Add SebastianGilPinzon/colab-mcp to Code Execution

Enhanced fork of Google's colab-mcp: all notebook tools visible at
startup (works with clients that ignore tools/list_changed), OAuth GPU
control (T4/L4/A100), and Windows support.
This commit is contained in:
Sebastian Gil Pinzon
2026-06-16 14:59:27 -05:00
parent daa005e19e
commit ec152037cc
+1
View File
@@ -506,6 +506,7 @@ Code execution servers. Allow LLMs to execute code in a secure environment, e.g.
- [pydantic/pydantic-ai/mcp-run-python](https://github.com/pydantic/pydantic-ai/tree/main/mcp-run-python) 🐍 🏠 - Run Python code in a secure sandbox via MCP tool calls
- [r33drichards/mcp-js](https://github.com/r33drichards/mcp-js) 🦀 🏠 🐧 🍎 - A Javascript code execution sandbox that uses v8 to isolate code to run AI generated javascript locally without fear. Supports heap snapshotting for persistent sessions.
- [rikarazome/prolog-reasoner](https://github.com/rikarazome/prolog-reasoner) [![rikarazome/prolog-reasoner MCP server](https://glama.ai/mcp/servers/rikarazome/prolog-reasoner/badges/score.svg)](https://glama.ai/mcp/servers/rikarazome/prolog-reasoner) 🐍 🏠 🍎 🪟 🐧 - SWI-Prolog execution for LLMs with CLP(FD), negation-as-failure, and recursion. Benchmarked 90% vs 73% LLM-only accuracy on 30 logic problems.
- [SebastianGilPinzon/colab-mcp](https://github.com/SebastianGilPinzon/colab-mcp) 🐍 🏠 🍎 🪟 🐧 - Control Google Colab notebooks and assign GPUs (T4/L4/A100) from any AI agent. Enhanced fork of Google's colab-mcp with all tools visible at startup, OAuth GPU control, and Windows support.
- [Sowiedu/Edict](https://github.com/Sowiedu/Edict) [![Sowiedu/Edict MCP server](https://glama.ai/mcp/servers/sowiedu/edict/badges/score.svg)](https://glama.ai/mcp/servers/sowiedu/edict) 📇 🏠 Agent-first programming language: agents produce JSON AST, the compiler validates, type-checks, effect-checks, verifies contracts via Z3/SMT, and compiles to WASM. 19 MCP tools for the full compile-and-execute loop.
- [yepcode/mcp-server-js](https://github.com/yepcode/mcp-server-js) 🎖️ 📇 ☁️ - Execute any LLM-generated code in a secure and scalable sandbox environment and create your own MCP tools using JavaScript or Python, with full support for NPM and PyPI packages