MCP开发框架
by w-jeon
A powerful MCP (Model Context Protocol) development framework for creating custom tools that interact with large language models. It provides a complete toolset for easily extending the functionality of Cursor IDE, enabling advanced features such as web content retrieval and file processing (PDF, Word, Excel).
Last updated: N/A
What is MCP开发框架?
The MCP开发框架 is a development framework that enables the creation of custom tools for interacting with large language models, specifically designed to extend the capabilities of the Cursor IDE.
How to use MCP开发框架?
The framework provides various tools accessible via specific commands. For example, use file /path/to/document for general file processing, pdf /path/to/document.pdf [mode] for PDF handling, word /path/to/document.docx for Word documents, excel /path/to/spreadsheet.xlsx for Excel files, and url https://example.com to fetch web content. Refer to the README for detailed usage instructions and parameter descriptions for each tool.
Key features of MCP开发框架
Comprehensive file processing (PDF, Word, Excel)
Web content retrieval
Intelligent file type recognition
Efficient document processing
Memory optimization and error handling
Use cases of MCP开发框架
Extending Cursor IDE functionality
Automating document processing tasks
Integrating web data into LLM workflows
Building custom tools for interacting with LLMs
Creating specialized data extraction pipelines
FAQ from MCP开发框架
How do I add a new tool?
How do I add a new tool?
Create a new Python file in the tools directory, inherit from BaseTool, register it with @ToolRegistry.register, and implement the execute method.
How do I deploy the framework?
How do I deploy the framework?
Docker deployment is recommended using docker compose up --build -d. Alternatively, you can use a traditional Python deployment by installing system and Python dependencies and running python -m mcp_tool.
What are the key dependencies?
What are the key dependencies?
Key dependencies include mcp, PyMuPDF, python-docx, pandas, openpyxl, httpx, anyio, and click.
How does the framework handle different PDF processing scenarios?
How does the framework handle different PDF processing scenarios?
The framework employs a multi-layered approach, starting with PyMuPDF for fast and accurate extraction, falling back to PymuPDF4llm, and finally using PyPDF2 as a last resort.
How are large files handled?
How are large files handled?
The framework uses temporary files to manage large files, automatically cleans up temporary resources, and processes large documents in chunks to optimize memory usage.