Decide which agents can act — then prove what happened with cryptographic evidence.
Trust-gated action for agent systems, with evidence clients and reviewers can verify independently.
Use AVP as a developer integration first, then roll it into live decisioning and evidence for production workflows.
For developers and product teams that want to add trust decisions and signed evidence without replacing their existing stack.
For teams that need to gate risky actions, detect trust degradation, and produce evidence others can verify independently.
Built for teams shipping agents into real workflows — especially when actions need to be gated, monitored, and proven afterward.
Give clients independent proof of what your agents did — without asking them to trust your dashboards or internal logs.
Check trust before delegation and monitor trust drift over time. Add coverage quickly with @avp_tracked when you’re ready to implement.
Add trust decisions before sensitive actions and signed evidence after them — on top of the stack you already use.
Produce client-ready evidence for agent actions that can be verified independently, including in high-stakes workflows. See Art. 9 / 12 / 13 / 14 / 50 mapping →
AVP separates the trust loop into three operational stages: decision before action, monitoring during execution, and evidence after the fact.
AVP is not a policy engine, MCP gateway, or sandbox runtime. It is the trust-decision and evidence layer between identity and action. AVP does not replace your identity or governance stack — it adds trust decisions before action and cryptographic evidence after action.
AVP turns agent actions into cryptographic evidence that clients, reviewers, and partners can verify independently — without relying on your internal infrastructure.
curl agentveil.dev/v1/reputation/{did}/credential?format=w3c
eddsa-jcs-2022 cryptosuite · RFC 8785 JCS · verifies with didkit, vc-js, Digital Bazaar
AVP does not replace observability. It adds what logs cannot: a trust decision before action, tamper-evident evidence after action, and proof others can verify independently.
can_trust() decision before actionIntegrate AVP without replacing your framework, identity provider, or observability tooling.
Frameworks
Interfaces
pip install agentveil — one line, zero config.
Any language. Full documentation & guides.
Claude Desktop, Cursor, Windsurf, VS Code. 12 tools.
Enterprise fit
AVP adds trust decisions before action and evidence after action — not a replacement for your current systems.
AVPProvider merged upstream into Microsoft Agent Governance Toolkit (PR #1010) as a TrustProvider implementation. →
Use AVP through production endpoints for reputation, trust checks, credentials, attestations, and audit verification.
Start with advisory checks. Move to gated actions when you’re ready.
| Method | Endpoint | Description |
|---|---|---|
| GET | /reputation/{did} | Score, confidence, risk assessment |
| GET | /reputation/{did}/trust-check | Advisory trust decision |
| GET | /reputation/{did}/credential | Signed offline credential (Ed25519) |
| GET | /reputation/{did}/velocity | Score trend (1d/7d/30d) |
| POST | /attestations | Submit peer rating |
| POST | /attestations/batch | Batch ratings (up to 50) |
| POST | /agents/register | Register new agent |
| GET | /cards | Search agents by capability |
| GET | /audit/verify | Chain integrity check |
Try AVP locally with a mock agent, then connect the same workflow to production when you’re ready.
# Install pip install agentveil # Try instantly — no server needed from agentveil import AVPAgent agent = AVPAgent.create(mock=True, name="my_agent") agent.register(display_name="My Agent") rep = agent.get_reputation(agent.did) print(rep) # {'score': 0.75, 'confidence': 0.5, ...}
# One line to auto-register and auto-attest an agent # inside an existing workflow from agentveil import avp_tracked @avp_tracked("https://agentveil.dev", name="my_agent", to_did="did:key:z6Mk...") def review_code(pr_url: str) -> str: return analyze(pr_url)
Start free in development. Pilot one trust-gated workflow. Expand to multi-team or high-stakes environments when you need full rollout.
For developers and teams validating trust checks in development
can_trust() advisory decisionsProve trust and evidence on a single critical action before wider rollout
Operationalize trust gating and independently verifiable evidence across production systems