cerberus

cerberussecurityai/cerberus

★ 1 stars Python AI/LLM Updated today

Client-side instrumentation for API and AI agent security monitoring. Django middleware, MCP server instrumentation, an Envoy AI Gateway OTLP bridge, and a MuleSoft Flex Gateway policy that capture request, tool-call and LLM traffic and stream it to Cerberus.

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Quick Install

Copy the config for your editor. Some servers may need additional setup — check the README.

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "cerberus": {
      "command": "uvx",
      "args": [
        "cerberus"
      ]
    }
  }
}

Or install with pip: pip install cerberus

README Excerpt

> Instrumentation for API and AI agent security monitoring: what your APIs served, what your agents called, and what your models spent. These are the libraries and gateway policies you add to your application, or place in front of it, so that a request, an MCP tool call, or an LLM call becomes something you can see. Each integration targets a different runtime and they all emit the same event schema, so they are interchangeable and can be mixed in one deployment.

Topics

agentic-aiai-agent-securityai-securityapi-securitydjangodjango-middlewareenvoyenvoy-ai-gatewayfastmcpflex-gatewayinstrumentationllm-securitymcpmodel-context-protocolmulesoft

cerberus

Quick Install

README Excerpt

Topics

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