This page is a collection of notes and links related to the Model Context Protocol (MCP), a proposed standard for extending managing context in large language models (LLMs) via external tools.
Resources
| Field | Category | Date | Link | Notes |
|---|---|---|---|---|
| Automation | Integration | 2025 | macos-automator-mcp | a macOS Node server that exposes AppleScript and JXA to MCP clients |
| Server Implementation | paws-on-mcp | yet another Python MCP server |
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| Document Processing | Integration | markitdown | a document-to-Markdown conversion tool/library useful for ingestion pipelines |
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| Documentation | Server Implementation | toMCP | turns any website or docs into an MCP server by extracting clean Markdown |
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| Extension Architecture | hyper-mcp | a powerful MCP server that leverages WebAssembly plugins |
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| Graphics | blender-mcp | a server that enables real-time interaction between Large Language Models and Blender using JSON over TCP. |
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| openscad-mcp | an MCP server for OpenSCAD that enables design automation and AI-assisted 3D modeling |
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| Integration | annas-mcp | an MCP server (and CLI) for searching and downloading documents from Anna’s Archive |
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| Fabric-Analytics-MCP | an MCP server that integrates with Microsoft Fabric for analytics tasks |
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| LLM Interoperability | Integration | mcp-llm-bridge | a bridge that connects MCP servers to OpenAI-compatible language models through a standardized interface. |
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| Language Bindings | Server Implementation | 2026 | swift-fast-mcp | a Swift builder API for quickly assembling MCP servers |
| 2025 | mcp-golang | a Go-based MCP server implementation |
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| Multi-agent Systems | Frameworks | agent-kit | an MCP framework for building multi-agent networks |
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| RAG | Server Implementation | haiku.rag | an agentic RAG toolkit that can run as an MCP server (document indexing, search, QA) |
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| Reverse Engineering | 2026 | ghidra-mcp | an MCP server that integrates with Ghidra for reverse engineering workflows |
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| Visual Programming | 2025 | node-red-mcp | a Node-RED MCP server with HomeAssistant understanding |