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Demos MCP
An MCP client calls three tools of an in-process MCP server (the mcp package's in-memory transport). Every
call_tool goes to the signer first: list_files runs, tracekit_demo_denied is denied (TK-DEMO-DENY) and the
client gets an error result and goes on, and tracekit_demo_ask waits inside call_tool until it is approved.
python examples/v2/mcp/agent.py --scripted # needs mcp
tracekit verify run.tkb --trust trust.jsonWhat the record shows. Each tool as mcp:files/<tool> with a signed policy.decision (flag, deny, ask); an
approval.request, approval and approval.consumed for the held one; a tool.result only for the two that ran.
verify.txt: Integrity: VERIFIED, Assurance: dev; ... approvals: self, as on any dev signer.
Why it matters. MCP servers are third-party code the agent reaches by name. The same policy and the same signed evidence cover them as the agent's own tools, with no change to the server; the dev policy's two demo rules stand in for your own rules on any MCP tool.
Generated from docs/ at v1.4.1. Edit the docs in the repository, not here.
Get started
- Quickstart: the v2 signer
- Quickstarts
- Quickstart: Claude Agent SDK
- Quickstart: a custom agent
- Quickstart: LangChain and LangGraph
- Quickstart: MCP client
- Quickstart: OpenAI Agents SDK
- Coding agents other than Claude Code
- tracekit doctor
- Walkthrough: Tracekit end to end
How it works
- How Tracekit works
- Overview
- The life of a tool call
- The evidence format
- Verification and assurance
- Witnesses and monitoring
- Policy
- Approvals
- Detection and containment
- Capture and completeness
- Custody
- Provenance and tracekit why
- Deployment and isolation
- Storage, durability and performance
- Integrations
- Security model
- Architecture
- tracekit why: architecture
Integrations
- Integrations
- Adapters
- OpenTelemetry
- Remote clients
- Kubernetes agent-sandbox
- agentgateway
- agentsh and Tracekit
- Browser Use
- Claude Agent SDK
- Claude Code's sandbox
- Codex's sandbox
- CrewAI
- Docker MCP Gateway
- E2B
- Falco
- Gemini CLI's sandbox
- Google ADK
- Haystack
- LangChain v1
- LiteLLM
- LlamaIndex
- MCP client
- microsandbox
- Microsoft Agent Framework
- OpenAI Agents SDK
- NVIDIA OpenShell
- Pydantic AI
- sandbox-runtime's proxy on its own
- Strands Agents
- Tetragon
- Vercel AI SDK
- Wassette
Policy and approvals
- Policy reference
- Approvals
- Findings
- Reading the model's reasoning
- Incidents and containment
- Webhooks
Deploy and operate
- Deploying the signer
- The signer as a container
- The signer on Kubernetes
- The compose stack
- Identity
- Tool executor
- MCP gateway
- LLM gateway
- Egress observation
- Witnesses
- Log monitor
- Record-key issuer
- Signer observability
- Viewer
- tracekit why: causal investigation and replay
- Migrating
- Platforms
Verify the evidence
- Reading a v2 verify report
- Evidence format v2
- Auditor guide
- Sample evidence bundle
- Signing
- What Tracekit guarantees
Security and privacy
- Threat model: the v2 signer
- Threat model: the v1 laptop signer
- HTTP security checklist
- Threat-model review packet
- Privacy
- Known limits and trade-offs
- What's stable
Compliance
- Compliance mapping
- EU AI Act
- ISO/IEC 42001
- NIST AI RMF and the Generative AI Profile
- OWASP Top 10 lists for LLM and agentic applications
Evaluation
Demos
- Demos
- Agent approvers within bounds
- Completeness and tamper evidence
- Detection and containment
- Network coverage: an egress observer
- Guardrails: allow, deny, or ask a person
- MCP tools, gated and recorded
- Prompt injection held by provenance
- Why: which input caused the action
Help