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A real-time security and policy mesh for MCP-based AI agent communication

Project description

🛡️ SentinelMesh

CI License: MIT Python

SentinelMesh is a real-time security, policy, and observability mesh for AI agents communicating via the Model Context Protocol (MCP).


🚀 Features

  • 🔎 Real-time monitoring of MCP agent-to-agent messages
  • 🔐 Prompt injection & sensitive context detection (YAML-defined rules)
  • ⚠️ Risk scoring with visual color tags
  • 📊 Streamlit dashboard with filters, charts, and risk summaries
  • 🧪 Log replay tool for forensic analysis
  • 🛑 Manual + auto-quarantine via blocklist
  • 🧱 Modular CLI structure (installed with setup.py)

📦 Installation

From your project root:

pip install -e .

🖥️ Dashboard

Launch the real-time Streamlit dashboard:

streamlit run sentinelmesh/dashboard/app.py

Features:

  • Realtime log table
  • Risk scoring with heatmap
  • Agent volume and risk timeline
  • Block/unblock agents live from the sidebar

🧰 CLI Tools

MCP Monitor:

sentinelmesh-cli

Monitors the log file and shows alerts in real time.


Log Replay:

sentinelmesh-replay --agent agent.hrbot.local --limit 10

Replay historical logs with filters.


⚙️ Config Files

  • sentinelmesh/rules/rules.yaml — security rules (phrases, context, regex)
  • sentinelmesh/rules/blocklist.yaml — blocked agents (manually set)
  • sentinelmesh/logs/mcp_traffic.log — live traffic log

📝 License

MIT © Rishit Goel

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