🚀 MCP Server for Document Processing
This MCP server lets AI assistants access and search your private documents, codebases, and latest tech info. It processes Markdown, text, and PDFs into a searchable database, extending AI knowledge beyond training data. Built with Docker, supports free and paid embeddings, and keeps AI updated with your data.
What is 🚀 MCP Server for Document Processing?
what is MCP Server? MCP Server is a document processing tool that implements a Model Context Protocol (MCP) server for processing Markdown and text files, chunking and tokenizing the content using embedding models. how to use MCP Server? To use MCP Server, clone the repository, set up your environment variables in a .env file, place your Markdown and text files in the data/ directory, and run the processing and server commands using Docker. key features of MCP Server? Processes Markdown and text files to generate embeddings. Exposes processed content through MCP tools for easy retrieval. Supports custom embedding models and configurations. use cases of MCP Server? Document processing for search and retrieval applications. Integration with Roo Code for enhanced content management. Custom embedding for specialized document types. FAQ from MCP Server? What file types does MCP Server support? By default, it supports Markdown (.md) and text (.txt) files, with the option to configure additional types. Do I need an API key to use MCP Server? An OpenAI API key is required for embeddings, while an Anthropic API key is optional for response generation. Can I use my own embedding model? Yes! You can implement a custom embedding function and configure it in the .env file.
As an MCP (Model Context Protocol) server, 🚀 MCP Server for Document Processing enables AI agents to communicate effectively through standardized interfaces. The Model Context Protocol simplifies integration between different AI models and agent systems.
How to use 🚀 MCP Server for Document Processing
To use MCP Server, clone the repository, set up your environment variables in a .env file, place your Markdown and text files in the data/ directory, and run the processing and server commands using Docker. key features of MCP Server? Processes Markdown and text files to generate embeddings. Exposes processed content through MCP tools for easy retrieval. Supports custom embedding models and configurations. use cases of MCP Server? Document processing for search and retrieval applications. Integration with Roo Code for enhanced content management. Custom embedding for specialized document types. FAQ from MCP Server? What file types does MCP Server support? By default, it supports Markdown (.md) and text (.txt) files, with the option to configure additional types. Do I need an API key to use MCP Server? An OpenAI API key is required for embeddings, while an Anthropic API key is optional for response generation. Can I use my own embedding model? Yes! You can implement a custom embedding function and configure it in the .env file.
Learn how to integrate this MCP server with your AI agents and leverage the Model Context Protocol for enhanced capabilities.
Use Cases for this MCP Server
- No use cases specified.
MCP servers like 🚀 MCP Server for Document Processing can be used with various AI models including Claude and other language models to extend their capabilities through the Model Context Protocol.
About Model Context Protocol (MCP)
The Model Context Protocol (MCP) is a standardized way for AI agents to communicate with various services and tools. MCP servers like 🚀 MCP Server for Document Processing provide specific capabilities that can be accessed through a consistent interface, making it easier to build powerful AI applications with complex workflows.
Browse the MCP Directory to discover more servers and clients that can enhance your AI agents' capabilities.