M

MCP Server For Document Processing

This project is a document processing server based on the Model Context Protocol (MCP) standard. By building a vector database and an MCP interface, it enables AI assistants to access external document resources and break through the knowledge limitations of large language models. The project includes two major components: a document processing pipeline and an MCP server. It supports multiple embedding models and file formats and can be applied to scenarios such as querying the latest technical documents and understanding private code libraries.
2.5 points
18

What is the MCP Document Processing Server?

The MCP Document Processing Server is a tool that helps you add the latest documents and private materials to the knowledge base of large language models. This allows AI assistants to access your specific content without relying on outdated training data.

How to use the MCP Document Processing Server?

You can start using it in just a few simple steps. First, prepare your documents, then run the server, and finally configure your AI assistant.

Applicable Scenarios

The MCP Document Processing Server is very suitable for application scenarios that require the latest framework documents, private code libraries, or technical specifications.

Main Features

Document Processing PipelineAutomatically read, split, embed, and store documents in a vector database.
Support for Multiple File TypesSupports Markdown, text, PDF, and Word documents.
Context RetrievalAllows AI assistants to retrieve relevant context when processing requests.
Custom ConfigurationSupports multiple embedding models and advanced settings.

Advantages and Limitations

Advantages
Expand the AI knowledge base to support the latest content
Support private documents and proprietary information
Improve the response accuracy of AI assistants
Limitations
Requires a certain technical background for configuration
May require more computing resources for large files

How to Use

Install Docker
Ensure that Docker is installed and running properly on your system.
Clone the Code Repository
Download and set up the code for the MCP Document Processing Server.
Configure Environment Variables
Edit the .env file to set API keys and other parameters.
Run the Processing Pipeline
Process documents and generate embeddings.
Build the Server
Build the MCP server image.
Connect the AI Assistant
Configure the AI assistant to use the MCP server.

Usage Examples

Upgrade AI's understanding of React 19Process the official documentation of React 19 to let the AI assistant understand its new features.
Debug issues in private API documentsUpload and process private API documents to help the AI assistant understand the specific implementation.

Frequently Asked Questions

How to install Docker?
Do I need an API key?
How to connect the AI assistant?

Related Resources

MCP Official Website
Learn more about the Model Context Protocol.
FireCrawl.dev
A powerful tool for crawling document websites.
GitHub Repository
The open-source code for the MCP Document Processing Server.
Installation
Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.
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