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82ch/MCP-Dandan

by Various

MCP Security Solution for Agentic AI — real-time proxying, behavior analysis, and malicious tool detection

8

MCP

82ch/MCP-Dandan

Added 1 June 2026

#ai-security #ai-security-tool #ai-tools #awesome-lists #mcp #mcp-gateway #mcp-guard #mcp-host

Overview

82ch/MCP-Dandan is an open-source Python tool that provides real-time proxying, behavior analysis, and malicious tool detection for MCP-based agentic AI systems. It acts as a security layer to monitor and filter interactions between agents and tools.

Best for

Best for
Developers building or deploying MCP servers who need a lightweight security layer for agent interactions.

Use cases

  • Securing MCP servers against unauthorized or harmful tool calls
  • Monitoring AI agent behavior in real time to detect anomalies
  • Integrating into agent workflows to block malicious actions

How to use

Install

npm run install-all

Tools exposed

  • npm
  • git

Example client config

MISTRAL_API_KEY=<your_mistral_api_key>

Notes

82ch/MCP-Dandan is an open-source Python tool that provides real-time proxying, behavior analysis, and malicious tool detection for MCP-based agentic AI systems. It acts as a security layer to monitor and filter interactions between agents and tools.

63 stars on GitHub. Last updated 2025-12-14. Licensed MIT.

Use cases

  • Securing MCP servers against unauthorized or harmful tool calls
  • Monitoring AI agent behavior in real time to detect anomalies
  • Integrating into agent workflows to block malicious actions

Pros

  • Real-time security monitoring for agent-tool interactions
  • Behavior analysis adds contextual threat detection
  • Open-source Python implementation for easy customization

Cons

  • Small community with only 63 stars, indicating limited adoption
  • Scope is narrow to MCP-based agent systems, not general AI security
  • May lack extensive documentation and production hardening

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Real-time security monitoring for agent-tool interactions
  • Behavior analysis adds contextual threat detection
  • Open-source Python implementation for easy customization

Cons

  • Small community with only 63 stars, indicating limited adoption
  • Scope is narrow to MCP-based agent systems, not general AI security
  • May lack extensive documentation and production hardening
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