🌌 MarkItDown MCP Server Integration with OpenWebUI and Claude Desktop
🌟 1. Introduction to MarkItDown MCP Server
🚀 Welcome to this comprehensive guide! This section will give you the foundational knowledge you need.
⚡ 1.1 What is MarkItDown MCP Server?
MarkItDown MCP Server is a specialized software component built upon the Model Context Protocol (MCP) framework. Its primary function is to facilitate the conversion of various digital file formats into Markdown, a lightweight markup language widely used for creating formatted text using a plain text editor.1 This conversion process is achieved through the utilization of an underlying utility known as “MarkItDown”.1 By acting as a bridge between different file types and the Markdown format, MarkItDown MCP Server enables AI-powered tools and applications to more easily process and understand the content contained within diverse document formats.1 The resulting Markdown output is often more readily digestible by large language models (LLMs) and other AI systems, streamlining workflows that involve document analysis, summarization, or content extraction. It is important to note that while MarkItDown MCP Server is the specific subject of this report, other similar tools exist within the MCP ecosystem. For instance, “Markdownify MCP Server” is another implementation that provides comparable functionalities, also focusing on the conversion of various file types and even web content into Markdown.3 This highlights a broader trend in developing specialized MCP servers to address specific needs within AI-driven workflows, such as document processing.
⚡ 1.2 Overview of the Model Context Protocol (MCP)
The Model Context Protocol (MCP) is an open standard that serves as a foundational layer for enabling seamless and secure communication between AI models and a wide array of external data sources and tools.1 It provides a standardized way for developers to establish robust, two-way connections that allow AI applications to access and interact with information residing in various locations.1 Often described as a “USB-C port for AI applications,” MCP aims to simplify the integration of AI with the broader digital landscape by offering a universal protocol for connecting AI models to diverse data sources and functionalities.6
The architecture of MCP is based on a client-host-server model.9 In this model, a host acts as the central coordinator, managing one or more clients. These clients, in turn, connect to servers that provide specific capabilities or access to data.9 This structured approach allows for a clear separation of concerns, enhancing modularity and security within AI systems.7 MCP facilitates the sharing of contextual information, the exposure of specialized tools, and the creation of composable integrations that can be tailored to specific AI workflows.9 Key components within the MCP framework include Prompts, which are predefined instructions for guiding AI interactions; Resources, which represent structured data providing context; and Tools, which are executable functions that allow AI models to perform actions or retrieve information.9 Understanding these core concepts of MCP is essential for effectively utilizing servers like MarkItDown MCP Server within AI applications.
⚡ 1.3 Scope of this Report
This report is specifically designed to provide a comprehensive understanding of MarkItDown MCP Server and its practical application within two prominent AI environments: OpenWebUI and Claude Desktop. The subsequent sections will delve into the intricacies of MarkItDown MCP Server, explore the underlying Model Context Protocol in greater detail, and provide step-by-step guidance on how to integrate and utilize MarkItDown MCP Server within both OpenWebUI and Claude Desktop.
🌟 2. Deep Dive into MarkItDown MCP Server
⚡ 2.1 How it Works: Architecture and Underlying Mechanisms
MarkItDown MCP Server operates as an intermediary component within the MCP ecosystem. It is designed to receive requests from MCP clients, such as Claude Desktop or OpenWebUI (when connected via a proxy), that require the conversion of files into Markdown format.1 Upon receiving such a request, the server leverages the capabilities of the “MarkItDown utility” to perform the actual transformation of the file’s content into Markdown.1 This utility likely contains the logic and algorithms necessary to parse various file formats and generate their Markdown equivalents. The interaction between an MCP client and the MarkItDown MCP Server typically occurs through specific MCP commands. One such command that the server is known to respond to is /md
⚡ 2.2 Supported File Formats for Conversion to Markdown
MarkItDown MCP Server demonstrates versatility by supporting a wide array of common digital document and media formats for conversion into Markdown.2 These supported formats include:
| File Format | Details |
|---|---|
| Portable Document Format | |
| PowerPoint | Presentation files |
| Word | Document files |
| Excel | Spreadsheet files |
| Images | Including extraction of EXIF metadata and OCR for text recognition |
| Audio | Including extraction of EXIF metadata and speech transcription |
| HTML | HyperText Markup Language files |
| CSV | Comma Separated Values files |
| JSON | JavaScript Object Notation files |
| XML | Extensible Markup Language files |
| ZIP files | Iterates over the contents of the archive |
This extensive list indicates the server’s capability to handle various types of documents, from standard office formats to web-related content and even multimedia files. It is worth noting that the underlying “markitdown” utility itself might possess the ability to convert an even broader range of formats, potentially including YouTube URLs and EPUB files.10 However, the specific set of formats exposed and handled by the MarkItDown MCP Server is what ultimately determines its practical utility within the MCP ecosystem.
⚡ 2.3 Available Tools and Features Offered by the Server
Based on the available research, the primary and perhaps the sole tool offered by MarkItDown MCP Server is the capability to convert a specified file into Markdown format.2 This functionality is invoked through the /md
⚡ 2.4 Installation Methods
Users have a couple of primary methods for installing and setting up MarkItDown MCP Server. One convenient option, particularly for those intending to use the server with Claude Desktop, is through automatic installation via a tool called Smithery.2 Smithery is likely a package or tool manager that simplifies the process of installing and configuring MCP servers for specific client applications like Claude Desktop. Alternatively, MarkItDown MCP Server can be installed manually.2 This typically involves cloning the server’s repository, assuming it is open-source and hosted on a platform like GitHub. Once the repository is cloned, the user would need to install any necessary dependencies. These dependencies would likely include the core “markitdown” utility itself, as well as any other libraries or software required for the server to run. The configuration example provided for Zed Editor in the research 2 offers valuable insight into how an MCP client defines and interacts with an MCP server. In this example, the client configuration specifies the command to execute to start the server, along with any arguments it requires. This demonstrates the fundamental principle of how MCP clients need to be informed about how to launch and communicate with the servers they intend to use.
🌟 3. Understanding the Model Context Protocol (MCP)
⚡ 3.1 Detailed Explanation of MCP Architecture: Host, Client, and Server
The Model Context Protocol (MCP) is structured around a three-tiered architecture comprising a Host, one or more Clients, and one or more Servers.7 Each of these components plays a distinct role in facilitating communication and interaction within the MCP ecosystem. The Host acts as the central orchestrator and manager within the MCP framework.9 Its responsibilities include creating and managing multiple Client instances, controlling the permissions and lifecycle of these clients, and enforcing security policies and consent requirements for all interactions. The host also handles user authorization decisions related to data access and tool usage, coordinates the integration of AI/LLM and the sampling process, and manages the aggregation of context across different clients. Essentially, the host provides the environment in which MCP clients operate and ensures that they adhere to defined rules and security measures.
Clients are created and managed by the host and are responsible for initiating and maintaining connections with Servers.9 Each client typically establishes a single, stateful session with each server it connects to. The key functions of a client include handling the negotiation of the protocol and the exchange of capabilities with the server, routing protocol messages bidirectionally between the host/application and the server, managing subscriptions to resources, and handling notifications from the server. Importantly, clients also maintain security boundaries between different servers they might be connected to. In essence, MCP clients are the AI applications or agents that need to access the specialized context and capabilities provided by MCP servers. They are characterized by their compatibility with the MCP protocol, allowing them to communicate using standardized interfaces like prompts, tools, and resources.
Servers are the entities that provide specialized context and capabilities to MCP clients.9 Their main functions include exposing resources, tools, and prompts via the MCP primitives, operating independently with focused responsibilities (such as providing access to a specific database or tool like file conversion), requesting sampling (LLM completions or generations) through client interfaces when needed, and respecting the security constraints imposed by the host and client. MCP servers act as wrappers or intermediaries that offer a standardized way to access various external systems, tools, and data sources, such as databases, customer relationship management (CRM) systems, local file systems, and version control systems.9 MarkItDown MCP Server, with its ability to convert files to Markdown, is a clear example of an MCP server that provides a specific tool to MCP clients.
⚡ 3.2 Key Components of MCP: Prompts, Resources, and Tools
The Model Context Protocol (MCP) defines three fundamental components that serve as the building blocks for interaction between clients and servers: Prompts, Resources, and Tools.6 These primitives enable rich and structured communication within the MCP ecosystem.
Tools are executable functions that are exposed by MCP servers.6 They allow AI models, operating through MCP clients, to interact with the external world and perform specific actions. These actions can range from simple tasks like retrieving the current time to more complex operations such as querying databases, interacting with APIs, or, in the case of MarkItDown MCP Server, converting files to Markdown.9 Tools in MCP are often designed to be model-controlled, meaning that the language model within the client application can decide when and how to invoke these tools based on its contextual understanding and the user’s prompts.9 The /md
Resources represent structured data or content that MCP servers can provide to clients.9 This can encompass a wide variety of data, including documents, database records, information retrieved from APIs, or even files residing on a local file system.9 Resources serve to provide additional context to the AI model, enabling it to generate more informed and relevant responses.9 For example, an MCP server might expose a resource containing the current weather information, which an AI assistant could then use to answer a user’s query about the forecast.
Prompts are pre-defined templates or instructions that MCP servers can offer to guide the interaction between the client (and the AI model it contains) and the server’s capabilities.9 These templates can help standardize common interactions and ensure that the AI model interacts with the server’s tools and resources in the intended way.9 For instance, an MCP server that interacts with a calendar might provide a prompt template for scheduling a new meeting, specifying the required parameters such as the date, time, and attendees. Prompts can be considered user-controlled tools that are invoked by the user through the client application. These three components – Tools, Resources, and Prompts – form the core of the Model Context Protocol, enabling a structured and versatile way for AI applications to access and utilize external information and functionalities.
⚡ 3.3 Lifecycle of an MCP Connection
The lifecycle of a connection between an MCP client and a server follows a well-defined sequence of phases to ensure proper communication and management of the session.9 These phases are Initialization, Operation, and Shutdown.
The Initialization phase is the crucial first step where the client and server establish a connection and agree on the parameters for their subsequent communication.9 This phase begins with the client sending an initialize request to the server, which includes information about the protocol version it supports, its own capabilities, and details about its implementation. The server then responds with its own capabilities and the protocol version it supports. If the client does not support the server’s protocol version, it should terminate the connection. Upon successful negotiation, the client sends an initialized notification to the server, indicating that it is ready for normal operations. The Operation phase is where the normal communication and exchange of messages between the client and server occur.9 During this phase, the client can send requests to the server, such as invoking a tool (like the file conversion tool in MarkItDown MCP Server), querying for resources, or triggering prompts. The server, in turn, processes these requests and sends back responses or notifications to the client.9 This is the main phase where the actual work and interaction facilitated by the MCP take place. The Shutdown phase involves the graceful termination of the connection between the client and the server.9 Typically, this process is initiated by the client, which signals its intent to close the connection. Instead of specific shutdown messages defined within the MCP protocol itself, the underlying transport mechanism used for communication (e.g., standard input/output for local processes or closing the HTTP connection for network-based communication) is used to indicate the termination of the session.
⚡ 3.4 Security Considerations when Using MCP Servers
Security is a significant aspect of the Model Context Protocol (MCP), and its architecture incorporates several features that allow for the implementation of security controls at various levels.7 The inherent separation of roles between hosts, clients, and servers creates defined points where security policies can be enforced.7
One key security consideration is the trust relationship between the host and the servers it allows its clients to connect to.7 The host has the authority to decide which servers are deemed trustworthy and should be permitted to interact with its clients.7 Similarly, individual clients maintain security boundaries between the different servers they might be connected to, preventing unauthorized access or interference between them. User consent and control are also paramount in the MCP framework.12 Users should be clearly informed about which MCP servers are being accessed by the AI applications they are using, and they should have the ability to approve or deny connections and data access.12 Client implementations play a crucial role in providing transparent user interfaces for managing these authorizations and ensuring that users can discern what data is being sent to and received from MCP servers.12
Standard security practices are also essential when working with MCP servers.7 For network-based communication, using TLS (Transport Layer Security) is recommended to ensure the secure transmission of data.7 If MCP servers require authentication (e.g., through API keys or tokens), these credentials should be stored and handled securely to prevent unauthorized access.7 Implementing authorization mechanisms such as Role-Based Access Control (RBAC) and Access Control Lists (ACLs) can further enhance security by ensuring that only permitted users or clients can access sensitive operations or data exposed by MCP servers.7
While MCP provides a solid foundation for secure interactions, it’s important to note that standard implementations might not include built-in approval workflows for critical operations or comprehensive audit trails for all interactions.7 Developers should be aware of these potential limitations and consider implementing additional security measures as needed, particularly when dealing with sensitive data or operations that require human oversight.7 Furthermore, implementing rate limiting and timeouts on both clients and servers can help mitigate the risk of resource exhaustion and denial-of-service (DoS) attacks.7 Continuous monitoring and logging of MCP interactions can also aid in detecting anomalies and facilitating security investigations.7
🌟 4. Integrating MarkItDown MCP Server with OpenWebUI
⚡ 4.1 OpenWebUI’s Support for External Tools and Integration Methods (OpenAPI, MCP)
OpenWebUI primarily focuses on integrating external tools and extending its functionalities through the OpenAPI specification.14 OpenAPI, formerly known as Swagger, is a widely adopted industry standard for describing and documenting RESTful APIs. By leveraging OpenAPI, OpenWebUI can seamlessly connect with a vast ecosystem of external services and tools that expose their capabilities through standard HTTP-based APIs.15 This approach allows developers to easily build or integrate servers that can enhance the capabilities of the language models used within OpenWebUI.14
While OpenWebUI’s primary integration method revolves around OpenAPI, it does not offer direct, native support for consuming MCP servers like MarkItDown MCP Server.15 However, to bridge this gap and enable OpenWebUI to interact with the growing number of powerful tools built on the MCP, OpenWebUI provides a crucial component: the MCP-to-OpenAPI proxy server.15 This proxy server acts as an intermediary, taking MCP-based tool servers and exposing their functionalities as standard REST API endpoints that adhere to the OpenAPI specification.16 This allows OpenWebUI to communicate with MCP servers without needing to implement the complexities of the MCP protocol itself. It is also important to note that OpenWebUI has a separate “Tools” feature, which allows users to integrate custom Python scripts to extend the LLM’s capabilities.17 These tools are distinct from both OpenAPI integrations and MCP servers. They are essentially Python functions that can be invoked by the LLM to perform specific tasks. While this provides another way to enhance OpenWebUI, it operates independently of the MCP ecosystem. The OpenWebUI community has acknowledged the increasing significance of the Model Context Protocol in the AI landscape and has discussed the potential benefits of adding direct MCP support in future versions.12 Such an enhancement could further streamline the integration of MCP-based tools. However, as of the current research, the recommended and most effective method for using MarkItDown MCP Server (and other MCP servers) with OpenWebUI is through the provided MCP-to-OpenAPI proxy server.
⚡ 4.2 Utilizing the MCP-to-OpenAPI Proxy Server for Seamless Integration
The MCP-to-OpenAPI proxy server (mcpo), provided by OpenWebUI, plays a vital role in enabling seamless integration between OpenWebUI and MCP-based tools like MarkItDown MCP Server.15 This proxy server functions by dynamically inspecting the connected MCP server, discovering the tools it offers, and automatically generating corresponding REST API endpoints that follow the OpenAPI specification. When the mcpo proxy server starts, it establishes a connection with the specified MCP server (in this case, MarkItDown MCP Server). It then queries the MCP server to understand the available tools and their functionalities. Based on the schemas provided by the MCP server, the proxy automatically builds FastAPI endpoints, which are essentially web addresses that OpenWebUI can use to interact with the MCP server’s tools. Furthermore, the mcpo proxy server also generates interactive API documentation using Swagger UI.16 This documentation is typically accessible through a /docs endpoint on the proxy server (e.g., http://localhost:8000/docs). It provides a user-friendly interface where developers can explore the available API endpoints, understand their parameters, and even test them directly in their web browser.16 This feature is incredibly valuable for understanding how to interact with the MarkItDown MCP Server’s capabilities through the proxy. By acting as a translator between the MCP protocol and the OpenAPI standard, the mcpo proxy server allows OpenWebUI to communicate with MarkItDown MCP Server (and other MCP servers) using standard HTTP requests. OpenWebUI doesn’t need to be aware of the underlying MCP protocol or handle its specific complexities.
⚡ 4.3 Step-by-Step Tutorial on Setting Up and Configuring the Proxy Server
To utilize MarkItDown MCP Server with OpenWebUI, you will first need to set up and configure the MCP-to-OpenAPI proxy server (mcpo). Here is a step-by-step tutorial to guide you through the process:
Step 1: Prerequisites:
Before you begin, ensure that you have the following prerequisites in place 16:
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Python 3.8 or higher: You need to have Python installed on your system. You can download it from the official Python website.
-
pip: The Python package installer (pip) should be installed along with Python.
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MarkItDown MCP Server: You need to have the MarkItDown MCP server installed on your system and know how to run it. Refer to Section 2.4 for installation methods.
-
(Optional but Recommended) uv: uv is a faster Python package installer and resolver. Installing it can potentially speed up the proxy server’s startup. You can install it using pip install uv. Step 2: Install mcpo:
Open your terminal or command prompt. If you have uv installed, it is recommended to use it for installing mcpo. Run the following command:
Bash
uvx mcpo
If you do not have uv installed, you can use pip:
Bash
pip install mcpo
Step 3: Run the Proxy Server:
Once mcpo is installed, you can run the proxy server, connecting it to your MarkItDown MCP Server. Open your terminal or command prompt and use the following command structure 16:
If using uv:
Bash
uvx mcpo —port <desired_port> — <command_to_run_markitdown_mcp_server>
If using pip (or if uvx is not working):
Bash
mcpo —port <desired_port> — <command_to_run_markitdown_mcp_server>
Replace <desired_port> with a port number you want the proxy server to listen on (e.g., 8000 is a common choice). The crucial part here is <command_to_run_markitdown_mcp_server>. This needs to be the exact command that you would use in your terminal to start the MarkItDown MCP server. For example, if you installed it manually and it has a main Python script named main.py, the command might be python main.py. If it’s run using uvx as seen in the Zed Editor example 2, it might be uvx run markitdown —directory /path/to/markitdown_mcp_server.
Example: Let’s assume you have a MarkItDown MCP server that you can run using the command python /path/to/your/markitdown_server/main.py. To run the mcpo proxy on port 8000, you would use the following command:
Bash
mcpo —port 8000 — python /path/to/your/markitdown_server/main.py
Step 4: Verify the Proxy is Running:
After executing the command, you should see output in your terminal indicating that the mcpo proxy server has started and is listening on the specified port. You can also verify that it’s working by opening your web browser and navigating to http://localhost:<desired_port>/docs (replace <desired_port> with the port you chose).
⚡ 4.4 Connecting the MarkItDown MCP Server (via the Proxy) to OpenWebUI
Once the mcpo proxy server is running and connected to your MarkItDown MCP Server, you can now connect it to OpenWebUI by following these steps 14:
Step 1: Open OpenWebUI:
Launch the OpenWebUI interface in your web browser. Step 2: Navigate to Settings:
Look for the settings icon (usually a gear icon ⚙️) in the OpenWebUI interface and click on it to access the settings menu. Step 3: Add a New Tool:
Within the settings menu, find a section related to “Tools,” “External Tools,” or “Tool Servers.” There should be an option to add a new tool server, often represented by an “Add” button or a plus sign (➕). Click on this option. Step 4: Enter the Proxy URL:
A dialog box or form will appear, asking you to provide the URL of your tool server. In this field, enter the URL where your mcpo proxy server is running. This will be in the format http://localhost:<desired_port>, where <desired_port> is the port number you specified when starting the proxy server in the previous section (e.g., http://localhost:8000).
Step 5: Save the Configuration:
After entering the proxy URL, click the “Save” button to apply the changes and save the tool server configuration in OpenWebUI. Step 6: Verify the Connection:
If the connection is successful, OpenWebUI should display an indicator in the message input area, typically a location pin icon (📍), indicating that a tool server is connected. You can click on this icon to view details about the connected tools. These tools will be the ones exposed by the MarkItDown MCP Server through the mcpo proxy. You should see information about the available API endpoints that you can now utilize within your OpenWebUI workflows.
⚡ 4.5 Practical Examples and Use Cases within OpenWebUI Workflows
With the MarkItDown MCP Server connected to OpenWebUI via the mcpo proxy, you can now leverage its file conversion capabilities within your AI interactions. Here are a couple of practical examples of how you might use it:
Example 1: Converting a Local PDF File:
You could instruct the AI model in OpenWebUI to convert a local PDF document to Markdown. This might involve a prompt like: “Please convert this PDF file to Markdown: [path/to/your/document.pdf]”.
When OpenWebUI processes this prompt, it will recognize that you have a tool server connected (the mcpo proxy). It will then look at the available tools exposed by the proxy. If the proxy has correctly exposed the /md command from the MarkItDown MCP Server as an OpenAPI endpoint, OpenWebUI should be able to utilize it. This might involve OpenWebUI sending a request to the proxy server, providing the path to the PDF file. The proxy would then forward this request to the MarkItDown MCP Server, which would perform the conversion and return the Markdown output back through the proxy to OpenWebUI. Example 2: Converting a DOCX File:
Similarly, you could ask OpenWebUI to convert a DOCX file to Markdown using a prompt like: “Can you convert this Word document to Markdown? [path/to/your/document.docx]”. The process would be similar to the PDF conversion. OpenWebUI would use the connected mcpo proxy to access the file conversion tool provided by the MarkItDown MCP Server, and the converted Markdown would be returned.
Considerations: The exact way you interact with the file conversion tool within OpenWebUI will depend on how the mcpo proxy exposes the /md command as an OpenAPI endpoint and how OpenWebUI handles tool usage. It might involve specific syntax or parameters within your prompts to indicate that you want to use this particular tool and to provide the necessary input (e.g., the file path).
🌟 5. Integrating MarkItDown MCP Server with Claude Desktop
⚡ 5.1 Claude Desktop’s Native Support for MCP Servers
Unlike OpenWebUI, Claude Desktop offers direct, built-in support for connecting to and utilizing MCP servers.8 This native integration means that you can directly configure Claude Desktop to communicate with MCP servers like MarkItDown MCP Server without the need for an intermediary proxy.2 This streamlined approach simplifies the setup process and allows for a more direct interaction between Claude and the external server. The primary mechanism for configuring these MCP server connections in Claude Desktop is through a JSON file named claude_desktop_config.json.18 This configuration file stores the details of the MCP servers that Claude Desktop should connect to, including information about how to start the server and any specific settings it might require. By manually creating or editing this file, users can instruct Claude Desktop to establish connections with various MCP servers, thereby extending its capabilities with the functionalities offered by those servers.
⚡ 5.2 Detailed Tutorial on Configuring the claude_desktop_config.json File
To integrate MarkItDown MCP Server with Claude Desktop, you will need to configure the claude_desktop_config.json file. Here is a detailed tutorial on how to do this 2:
Step 1: Locate the Configuration File:
The claude_desktop_config.json file is typically located in the following directories depending on your operating system:
-
Windows: %AppData%\Claude Desktop\ To access this directory, you can open File Explorer, type %AppData% in the address bar, and then navigate to the Claude Desktop folder. You might need to enable the viewing of hidden files and folders in File Explorer settings to see the AppData folder.21
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macOS: /Users/[Your Username]/Library/Application Support/Claude/ Replace [Your Username] with your actual username on the system.22 The Library folder is often hidden, so you might need to use the “Go” menu in Finder, select “Go to Folder…”, and enter the path to access it. If the claude_desktop_config.json file does not exist in these locations, you will need to create it using a plain text editor. Step 2: Open the Configuration File:
Once you have located the file (or created a new one), open it using a plain text editor such as Notepad (on Windows) or TextEdit (on macOS). Avoid using rich text editors like Microsoft Word, as they might introduce formatting that can cause issues with the JSON file. Step 3: Add the MarkItDown MCP Server Configuration:
The configuration for MCP servers in Claude Desktop is done within the “mcpServers” section of the claude_desktop_config.json file. If this section doesn’t exist, you will need to create it as a top-level key in the JSON structure. Under the “mcpServers” key, you will add an entry for the MarkItDown MCP server. This entry will consist of a unique name that you choose for the server (e.g., “markitdown”) followed by an object containing the server’s configuration details. Based on the example provided for Zed Editor 2, a basic configuration for MarkItDown MCP Server might look like this:
JSON
{ “mcpServers”: { “markitdown”: { “settings”: {}, “command”: { “path”: “<path_to_markitdown_server_executable>”, “args”: [“<arguments_if_any>”] } } } }
You will need to replace <path_to_markitdown_server_executable> with the actual absolute path to the executable file or script that starts the MarkItDown MCP server on your system. The <arguments_if_any> array would contain any command-line arguments that the server requires to run correctly. If the MarkItDown MCP server is intended to be run using uvx (as suggested in the Zed Editor example for another MCP server 2), the configuration might look like this:
JSON
{ “mcpServers”: { “markitdown”: { “settings”: {}, “command”: { “path”: “uvx”, “args”: [“markitdown”, “—directory”, “/path/to/markitdown_mcp_server”] } } } }
In this case, you would replace /path/to/markitdown_mcp_server with the actual path to the directory where the MarkItDown MCP server is installed. The exact configuration details will depend on how you installed the MarkItDown MCP server and how it is designed to be run. You should consult the server’s documentation or any instructions provided with it for the specific configuration parameters required. Step 4: Save the Configuration File:
After you have added the configuration for the MarkItDown MCP server to the claude_desktop_config.json file, make sure to save the changes. Step 5: Restart Claude Desktop:
It is crucial to completely close the Claude Desktop application after modifying the configuration file. This means not just closing the main window but also ensuring that the application is not running in the system tray (on Windows) or the menu bar (on macOS). Once you have confirmed that it’s fully closed, restart the Claude Desktop application. This will allow it to load the new configuration and establish a connection with the MarkItDown MCP server.
⚡ 5.3 Step-by-Step Instructions for Installing MarkItDown MCP Server for Claude Desktop
Here are step-by-step instructions for installing MarkItDown MCP Server for use with Claude Desktop, covering both potential automatic and manual methods 2:
Option 1: Automatic Installation via Smithery (if available):
According to the research 2, MarkItDown MCP Server can be installed automatically for Claude Desktop using a tool called Smithery. If this option is still available within your version of Claude Desktop, follow these general steps:
1. Open the Claude Desktop application. 2. Look for a menu or settings option related to “Integrations,” “MCP Servers,” or potentially a tool manager like “Smithery.” This might be located in the application’s preferences or settings panel. 3. If you find Smithery or a similar tool, open it and search for “MarkItDown MCP Server.” 4. If the server is listed, select it and click on the “Install” or “Add” button. 5. Follow any on-screen prompts or instructions provided by Smithery to complete the installation. 6. Once the installation is complete, you might need to restart Claude Desktop as described in Section 5.2.
⚡ Option 2: Manual Installation:
1. Clone the Repository (if open-source): If the MarkItDown MCP Server’s code is hosted on a platform like GitHub, navigate to the repository page using a web browser and look for a “Clone” button. Copy the repository URL. Open your terminal or command prompt, navigate to the directory where you want to store the server’s code, and use the git clone <repository_url> command to download the code to your local machine. 2. Install Dependencies: Once the repository is cloned, navigate into the newly created directory in your terminal or command prompt. Look for a file named requirements.txt (if the server is written in Python) or package.json or pnpm-lock.yaml (if it’s in JavaScript or TypeScript).
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For Python: If you find requirements.txt, run the command pip install -r requirements.txt to install the necessary Python packages. You might need to have Python and pip installed on your system.
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For Node.js/TypeScript: If you find package.json or pnpm-lock.yaml, you will likely need to have Node.js and npm (or pnpm) installed. Run the command npm install or pnpm install to download and install the required JavaScript packages. If the server is written in TypeScript, you might also need to build the project using a command like npm run build or pnpm run build. 3. Note the Server’s Execution Command: After installing the dependencies, you need to determine how to start the MarkItDown MCP Server. This information is usually provided in the server’s documentation (often in a README file). Look for instructions on running or starting the server. 4. Configure claude_desktop_config.json: Follow the steps outlined in Section 5.2 to add the MarkItDown MCP Server to the claude_desktop_config.json file. Use the execution command you noted in the previous step to configure the “command” and “args” within the JSON structure. Ensure that you provide the correct path to the server’s main script or executable. 5. Restart Claude Desktop: After configuring the claude_desktop_config.json file, completely close and then restart the Claude Desktop application for the changes to take effect. 6. Verification: After restarting, you should look for an MCP integration icon in the Claude Desktop interface. This icon might appear in the bottom right corner of the input box.18 Clicking on this icon should display a panel listing the installed MCP servers, and you should see your MarkItDown MCP server listed there.
⚡ 5.4 Examples Demonstrating the Usage of MarkItDown MCP Server within Claude Desktop
Once you have successfully installed and configured the MarkItDown MCP Server with Claude Desktop, you can start using it to convert files to Markdown. Here are a couple of examples of how you might interact with it:
Example 1: Converting a Local PDF File:
To convert a local PDF file to Markdown, you can simply ask Claude Desktop to do so using a natural language prompt. For example, you might say: “Claude, please convert this PDF document to Markdown: /path/to/your/document.pdf”.
Claude Desktop, if it has correctly connected to the MarkItDown MCP Server, should recognize this request and send a command to the server (likely using the /md command followed by the file path, as mentioned in 2).
Example 2: Converting a DOCX File:
Similarly, you can ask Claude to convert a DOCX file. The prompt might look like: “Could you convert this Word document to Markdown for me? /path/to/your/document.docx”. Again, Claude should utilize the configured MarkItDown MCP Server to perform the conversion, and the resulting Markdown would be provided to you. The exact phrasing of the prompts might vary slightly depending on how Claude Desktop and the MarkItDown MCP Server are designed to interact. However, the general principle is that you can use natural language to instruct Claude to perform file conversions, and it will leverage the capabilities of the connected MCP server to fulfill your request. You might see an indication in Claude Desktop’s interface (e.g., a message or a log entry if developer mode is enabled) that it is using an external tool for this task.
🌟 6. Practical Implementation Examples and Tutorials
⚡ 6.1 Scenario 1: Converting a Local PDF File to Markdown
⚡ OpenWebUI (via Proxy):
1. Ensure the mcpo proxy server is running, connected to your MarkItDown MCP Server, and listening on a specific port (e.g., 8000). The command to run the proxy would look something like: mcpo —port 8000 — python /path/to/your/markitdown_server/main.py. 2. Ensure you have added the proxy server URL (http://localhost:8000) to OpenWebUI’s tool server settings. 3. In the OpenWebUI chat interface, use a prompt like: “Please convert this PDF file to Markdown: /path/to/your/document.pdf”. 4. OpenWebUI should send a request to the mcpo proxy, which in turn communicates with the MarkItDown MCP Server to convert the specified PDF file. 5. The converted Markdown content should then be returned and displayed in OpenWebUI.
⚡ Claude Desktop:
1. Ensure you have configured the claude_desktop_config.json file with the correct details for your MarkItDown MCP Server (as described in Section 5.2) and that Claude Desktop has been restarted. 2. In the Claude Desktop chat interface, use a prompt like: “Claude, please convert this PDF document to Markdown: /path/to/your/document.pdf”. 3. Claude Desktop should recognize this request and utilize the configured MarkItDown MCP Server to perform the conversion. 4. The resulting Markdown text should then be available within the Claude Desktop chat or context.
⚡ 6.2 Scenario 2: Converting a DOCX File to Markdown
⚡ OpenWebUI (via Proxy):
1. Follow the same initial steps as in Scenario 1 for OpenWebUI. 2. In the OpenWebUI chat interface, use a prompt like: “Can you convert this Word document to Markdown? /path/to/your/document.docx”. 3. The process should be similar to the PDF conversion, with the DOCX file being sent to the MarkItDown MCP Server via the proxy. 4. The converted Markdown output should be displayed in OpenWebUI.
⚡ Claude Desktop:
1. Follow the same initial steps as in Scenario 1 for Claude Desktop. 2. In the Claude Desktop chat interface, use a prompt like: “Could you convert this Word document to Markdown for me? /path/to/your/document.docx”. 3. Claude Desktop should use the configured MarkItDown MCP Server to convert the DOCX file. 4. The resulting Markdown text should be available in Claude Desktop.
⚡ 6.3 Scenario 3: Converting a Web Page to Markdown
Based on the research, the specific “MarkItDown MCP Server” as described primarily focuses on converting local files.2 There is no explicit mention of direct support for converting web pages from URLs. If this functionality is required, you might need to explore alternative MCP servers like “Markdownify MCP Server” 3 or “Markdown Downloader” 25, which specifically advertise the ability to convert web content to Markdown. If you are using an alternative server that supports web page conversion, the process for integration with OpenWebUI (via proxy) and Claude Desktop would be similar to the examples above, but the prompt would involve providing the URL of the web page instead of a local file path. For example, in OpenWebUI, you might use a prompt like: “Please convert this webpage to Markdown: https://www.example.com/blog-post”.
⚡ 6.4 Code Snippets and Configuration Examples
⚡ Example mcpo Command (OpenWebUI):
Assuming your MarkItDown MCP Server is a Python script named main.py located at /path/to/your/markitdown_server/, you would run the mcpo proxy using the following command (adjust the path and port as needed):
Bash
mcpo —port 8000 — python /path/to/your/markitdown_server/main.py
⚡ Example claude_desktop_config.json Entry (Claude Desktop):
Assuming your MarkItDown MCP Server is run using uvx and its code is located in /path/to/your/markitdown_mcp_server/, your entry in the claude_desktop_config.json file might look like this:
JSON
{ “mcpServers”: { “markitdown”: { “settings”: {}, “command”: { “path”: “uvx”, “args”: [“markitdown”, “—directory”, “/path/to/your/markitdown_mcp_server”] } } } }
Remember to replace the placeholder paths with the actual paths on your system.
🌟 7. Troubleshooting and Best Practices
⚡ 7.1 Common Issues Encountered During Setup and Integration
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Proxy Server Not Starting (OpenWebUI): Ensure that Python is installed correctly, the mcpo package is installed, and the command to run your MarkItDown MCP Server is correct. Check for any error messages in the terminal where you are running the proxy.
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OpenWebUI Not Connecting to Proxy: Double-check that the URL you entered in OpenWebUI’s tool server settings is correct and matches the port on which the mcpo proxy is running.14 Also, ensure that the proxy server is actually running.
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Claude Desktop Not Connecting to MCP Server: Verify that the paths in your claude_desktop_config.json file are correct.23 Ensure that you have completely quit and restarted Claude Desktop after making changes to the configuration file.18 Look for the MCP icon in the Claude Desktop interface to confirm if servers are detected.23 If you encounter a “Could not attach to MCP server” error, double-check all paths and try running Claude Desktop as an administrator.
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File Path Errors: When providing file paths in your prompts, ensure that the paths are correct and accessible by the respective application (OpenWebUI via proxy, or Claude Desktop and the MCP server).
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Incorrect Server Execution Command: If the command specified in the claude_desktop_config.json or used to run the mcpo proxy is incorrect, the MCP server will not start or function properly. Consult the MarkItDown MCP Server’s documentation for the correct execution command.
⚡ 7.2 Tips for Ensuring Optimal Performance and Reliability
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Run both the mcpo proxy server and the MarkItDown MCP Server on stable hardware with sufficient resources.
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Ensure that all dependencies for both the proxy and the MCP server are installed correctly.
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If available, monitor the logs of both the proxy server and the MarkItDown MCP Server for any errors or performance issues.
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Keep your installations of Python, mcpo, OpenWebUI, Claude Desktop, and the MarkItDown MCP Server updated to the latest versions to benefit from bug fixes and performance improvements.
⚡ 7.3 Security Recommendations for Using External MCP Servers
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Be cautious about the MCP servers you connect to, especially if they require access to local files or other sensitive data. Understand the permissions you are granting to these servers.12
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Consider running MCP servers in a sandboxed environment or with limited permissions to minimize potential security risks.
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If a server requires API keys or other credentials, ensure that these are stored securely and not exposed unnecessarily.
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Regularly review the configuration of your MCP server connections in both OpenWebUI and Claude Desktop to ensure that only trusted servers are enabled.
🌟 8. Conclusion
The integration of MarkItDown MCP Server with both OpenWebUI and Claude Desktop offers a valuable capability for users who need to convert various file formats to Markdown within their AI workflows. While the integration approaches differ – OpenWebUI relies on the MCP-to-OpenAPI proxy server (mcpo), and Claude Desktop offers native MCP support – both methods enable users to leverage the document conversion functionalities of the MarkItDown MCP Server. OpenWebUI users can benefit from the proxy’s ability to translate the MCP protocol into standard OpenAPI endpoints, allowing for seamless interaction with the server through a familiar interface. Claude Desktop users can take advantage of the direct MCP support, configuring the server connection through the claude_desktop_config.json file for a more direct communication pathway. The choice between these two platforms for utilizing MarkItDown MCP Server will likely depend on the user’s preferred AI environment and their technical comfort level with setting up and managing the proxy server in the case of OpenWebUI. Regardless of the chosen platform, the ability to convert a wide range of file formats to Markdown opens up numerous possibilities for enhanced document processing, analysis, and utilization within AI-powered applications.
🔧 Works cited
1. Converts various file formats to Markdown using the MarkItDown utility and can be integrated with MCP clients for seamless document processing and conversion. - Reddit, accessed on April 3, 2025, https://www.reddit.com/r/mcp/comments/1icgekn/markitdown_mcp_server_converts_various_file/ 2. MarkItDown MCP Server - Glama, accessed on April 3, 2025, https://glama.ai/mcp/servers/sbc6bljjg5 3. Markdownify MCP Server - zach.dev, accessed on April 3, 2025, https://zach.dev/blog/markdownify-mcp 4. zcaceres/markdownify-mcp: A Model Context Protocol … - GitHub, accessed on April 3, 2025, https://github.com/zcaceres/markdownify-mcp 5. Model Context Protocol - GitHub, accessed on April 3, 2025, https://github.com/modelcontextprotocol 6. Model context protocol (MCP) - OpenAI Agents SDK, accessed on April 3, 2025, https://openai.github.io/openai-agents-python/mcp/ 7. AI Model Context Protocol (MCP) and Security - Cisco Community, accessed on April 3, 2025, https://community.cisco.com/t5/security-blogs/ai-model-context-protocol-mcp-and-security/ba-p/5274394 8. Model Context Protocol (MCP) - Anthropic API, accessed on April 3, 2025, https://docs.anthropic.com/en/docs/agents-and-tools/mcp 9. The Model Context Protocol (MCP) — A Complete Tutorial | by Dr …, accessed on April 3, 2025, https://medium.com/@nimritakoul01/the-model-context-protocol-mcp-a-complete-tutorial-a3abe8a7f4ef 10. microsoft/markitdown: Python tool for converting files and office documents to Markdown. - GitHub, accessed on April 3, 2025, https://github.com/microsoft/markitdown 11. Claude MCP - Model Context Protocol, accessed on April 3, 2025, https://www.claudemcp.com/ 12. Enh: Add support for Model Context Protocol (MCP) #7363 - GitHub, accessed on April 3, 2025, https://github.com/open-webui/open-webui/discussions/7363 13. MCP Server Development Protocol - Cline Documentation, accessed on April 3, 2025, https://docs.cline.bot/mcp-servers/mcp-server-from-scratch 14. Open WebUI Integration | Open WebUI, accessed on April 3, 2025, https://docs.openwebui.com/openapi-servers/open-webui/ 15. OpenAPI Tool Servers | Open WebUI, accessed on April 3, 2025, https://docs.openwebui.com/openapi-servers/ 16. MCP Support | Open WebUI, accessed on April 3, 2025, https://docs.openwebui.com/openapi-servers/mcp/ 17. Tools | Open WebUI, accessed on April 3, 2025, https://docs.openwebui.com/features/plugin/tools/ 18. The Easiest Way to Set Up MCP with Claude Desktop and Docker Desktop, accessed on April 3, 2025, https://dev.to/suzuki0430/the-easiest-way-to-set-up-mcp-with-claude-desktop-and-docker-desktop-5o 19. Supercharge Your Claude Desktop Experience: How MCP Servers Create a Claude Code-Like Environment | by Ravi Kiran Vemula | Feb, 2025 | Medium, accessed on April 3, 2025, https://medium.com/@vrknetha/supercharge-your-claude-desktop-experience-how-mcp-servers-create-a-claude-code-like-environment-7e984c802107 20. Extending Claude with External Tools: MCPs in Action - Goat Review, accessed on April 3, 2025, https://goatreview.com/extend-claude-model-context-protocol/ 21. Turn Claude into a BEAST with MCP For Your Desktop (Insane AI Power!) - YouTube, accessed on April 3, 2025, https://www.youtube.com/watch?v=ZELurOv4YiQ 22. My Claude Workflow Guide: Advanced Setup with MCP External Tools : r/ClaudeAI - Reddit, accessed on April 3, 2025, https://www.reddit.com/r/ClaudeAI/comments/1ji8ruv/my_claude_workflow_guide_advanced_setup_with_mcp/ 23. MCP-Windows · GitHub, accessed on April 3, 2025, https://gist.github.com/feveromo/7a340d7795fca1ccd535a5802b976e1f 24. 5 - MCP Installer Tool: Install MCP Servers Automatically ⚙️ - YouTube, accessed on April 3, 2025, https://www.youtube.com/watch?v=juJXe0JRRlc 25. Markdown Downloader MCP Server - GitHub, accessed on April 3, 2025, https://github.com/dazeb/markdown-downloader