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replied to their post 5 days ago
13 Awesome MCP Servers MCP changed how agents connect with tools. After writing the most read explanation of MCP on Hugging Face (https://huggingface.co/blog/Kseniase/mcp), we chose this 13 awesome MCP servers that you can work with: 1. Agentset MCP -> https://github.com/agentset-ai/mcp-server For efficient and quick building of intelligent, doc-based apps using open-source Agentset platform for RAG 2. GitHub MCP Server -> https://github.com/github/github-mcp-server Integrates GitHub APIs into your workflow, allowing to build AI tools and apps that interact with GitHub's ecosystem 3. arXiv MCP -> https://github.com/andybrandt/mcp-simple-arxiv Allows working with research papers on arXiv through effective search and access to their metadata, abstracts, and links 4. MCP Run Python -> https://github.com/pydantic/pydantic-ai/tree/main/mcp-run-python Enables to run Python code in a sandbox via Pyodide in Deno, so it can be isolated from the rest of the operating system 5. Safe Local Python Executor -> https://github.com/maxim-saplin/mcp_safe_local_python_executor A lightweight tool for running LLM-generated Python code locally, using Hugging Face’s LocalPythonExecutor (from smolagents framework) and exposing it via MCP for AI assistant integration 6. Cursor MCP Installer -> https://github.com/matthewdcage/cursor-mcp-installer Allows to automatically add MCP servers to Cursor for development convenience 7. Basic Memory -> https://memory.basicmachines.co/docs/introduction This knowledge management system connects to LLMs and lets you build a persistent semantic graph from AI conversations with AI agents Read further in the comments πŸ‘‡ If you like it, also subscribe to the Turing Post: https://www.turingpost.com/subscribe
posted an update 5 days ago
13 Awesome MCP Servers MCP changed how agents connect with tools. After writing the most read explanation of MCP on Hugging Face (https://huggingface.co/blog/Kseniase/mcp), we chose this 13 awesome MCP servers that you can work with: 1. Agentset MCP -> https://github.com/agentset-ai/mcp-server For efficient and quick building of intelligent, doc-based apps using open-source Agentset platform for RAG 2. GitHub MCP Server -> https://github.com/github/github-mcp-server Integrates GitHub APIs into your workflow, allowing to build AI tools and apps that interact with GitHub's ecosystem 3. arXiv MCP -> https://github.com/andybrandt/mcp-simple-arxiv Allows working with research papers on arXiv through effective search and access to their metadata, abstracts, and links 4. MCP Run Python -> https://github.com/pydantic/pydantic-ai/tree/main/mcp-run-python Enables to run Python code in a sandbox via Pyodide in Deno, so it can be isolated from the rest of the operating system 5. Safe Local Python Executor -> https://github.com/maxim-saplin/mcp_safe_local_python_executor A lightweight tool for running LLM-generated Python code locally, using Hugging Face’s LocalPythonExecutor (from smolagents framework) and exposing it via MCP for AI assistant integration 6. Cursor MCP Installer -> https://github.com/matthewdcage/cursor-mcp-installer Allows to automatically add MCP servers to Cursor for development convenience 7. Basic Memory -> https://memory.basicmachines.co/docs/introduction This knowledge management system connects to LLMs and lets you build a persistent semantic graph from AI conversations with AI agents Read further in the comments πŸ‘‡ If you like it, also subscribe to the Turing Post: https://www.turingpost.com/subscribe
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