Post
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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 👇
If you like it, also subscribe to the Turing Post: https://www.turingpost.com/subscribe
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 👇
If you like it, also subscribe to the Turing Post: https://www.turingpost.com/subscribe