hellob1889/Pandaone-AI-Agent
by Various
Pandaone Guard — Free open-source MCP server for AI code audit. L1-L6 defense (file lock + audit log + pre-commit hooks) for Claude/Cursor/Trae. Local stdio, no API key, MIT.
MCP
hellob1889/Pandaone-AI-Agent
Added 21 Sept 2026
Overview
Pandaone Guard is a free, open-source MCP server for AI code audit. It provides L1-L6 defense mechanisms including file locking, audit logging, and pre-commit hooks for AI coding tools like Claude, Cursor, and Trae. Runs locally via stdio with no API key required, licensed under MIT.
Best for
Best for
Developers using Claude, Cursor, or Trae who want a local, no-key MCP guard for AI code changes.
Use cases
- Set up a local MCP server for auditing AI-generated code changes
- Enforce file locks and pre-commit hooks across Claude, Cursor, or Trae workflows
- Maintain an audit log of AI code edits without sending data to external services
How to use
Install
pip install pandaone-guard Tools exposed
PANDAX_FP_PASSWORDPANDAX_LANGPANDAONE_SKIP_GIT_CHECKNO_COLORpandaone-mcp
Tested with
Claude Code, Cursor, ChatGPT
Notes
Pandaone Guard is a free, open-source MCP server for AI code audit. It provides L1-L6 defense mechanisms including file locking, audit logging, and pre-commit hooks for AI coding tools like Claude, Cursor, and Trae. Runs locally via stdio with no API key required, licensed under MIT.
0 stars on GitHub. Last updated 2026-09-21. Licensed MIT.
Use cases
- Set up a local MCP server for auditing AI-generated code changes
- Enforce file locks and pre-commit hooks across Claude, Cursor, or Trae workflows
- Maintain an audit log of AI code edits without sending data to external services
Pros
- No API key required, runs entirely local via stdio
- Free and open-source under MIT license
- Works with multiple AI coding tools (Claude, Cursor, Trae)
Cons
- Zero stars on GitHub, indicating minimal community adoption or validation
- Defense scope limited to file locking, audit logging, and pre-commit hooks
- Requires a Python environment to run
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- No API key required, runs entirely local via stdio
- Free and open-source under MIT license
- Works with multiple AI coding tools (Claude, Cursor, Trae)
Cons
- Zero stars on GitHub, indicating minimal community adoption or validation
- Defense scope limited to file locking, audit logging, and pre-commit hooks
- Requires a Python environment to run
Pairs with
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