Agent Trust MCP Server

Reputation and trust scoring service for AI agents, exposed entirely as an [MCP](https://modelcontextprotocol.io/) server. Evaluate counterparties

Local serverstdioPython

What is the Agent Trust MCP Server?

Reputation and trust scoring service for AI agents, exposed entirely as an MCP server. Evaluate counterparties before

What it needs from you

  • Python 3.13+ - PostgreSQL 16 - Redis 7 - uv package manager

Recorded tools

  • discover — Returns the complete service catalog: available tools, auth methods, score types, interaction types, rate limits, and a quickstart guide. Call this first when connecting.
  • register_agent — 1. AgentAuth -- pass access_token from AgentAuth 2. Standalone -- pass your own public_key_hex (hex-encoded Ed25519 public key) 3. Auto-generate -- omit both to get a keypair generated for you
  • generate_agent_token — The generate_agent_token tool exposed by this server.
  • whoami — The whoami tool exposed by this server.
  • get_agent_profile — The get_agent_profile tool exposed by this server.
  • search_agents — Search agents by trust score, capabilities, and interaction count.
  • link_agentauth — Link an existing standalone profile to an AgentAuth identity, merging interaction history. The canonical agent_id after linking is always the original standalone UUID — the AgentAuth UUID is stored as agentauth_id in met
  • verify_link_proof — Preflight check: validate a link_agentauth proof without writing to the database. Runs the same validation steps (token authenticity, key lookup, proof signature, expiry, already-linked check) but never persists any chan
  • agent_status — One-call status snapshot combining identity, trust scores, pending confirmation count, and active attestations. Useful as a dashboard or health check.
  • check_trust — Primary tool for evaluating an agent before a transaction. Returns a score (0.0-1.0), confidence (0.0-1.0), interaction count, and a plain-language explanation.
  • check_trust_batch — The check_trust_batch tool exposed by this server.
  • compare_agents — The compare_agents tool exposed by this server.
  • get_score_breakdown — Detailed Bayesian factors behind a score: raw score, dispute penalty, alpha/beta parameters, interaction weights.

More MCP options

Compare MCP servers by category, or browse hosted MCP servers if you prefer an endpoint over a local process.

Maintainer setup documentation.

Recorded tools

Check the linked publisher documentation and your connected client's tool list. Names and availability can vary with the server version and account permissions.

ToolWhat it does
register_agent
generate_agent_token
get_agent_profile
search_agents
link_agentauth
verify_link_proof
agent_status
check_trust
check_trust_batch
compare_agents
get_score_breakdown
report_interaction
confirm_interaction
list_pending_confirmations
get_interaction_history
file_dispute
resolve_dispute
issue_attestation
list_my_attestations
verify_attestation
sybil_check

How to install the Agent Trust MCP Server

{
  "mcpServers": {
    "agent-trust": {
      "url": "https://agent-trust.radi.pro/mcp"
    }
  }
}

From the project documentation. Replace placeholders and example paths before connecting.

Configuration

  • Python 3.13+ - PostgreSQL 16 - Redis 7 - uv package manager

Example prompts to try

  • “Use Agent Trust to Discovery.”
  • “Use Agent Trust to discover.”
  • “Use Agent Trust to register agent.”

Frequently asked questions

Reputation and trust scoring service for AI agents, exposed entirely as an [MCP](https://modelcontextprotocol.io/) server. Evaluate counterparties before Confirm the tools offered by your installed version in the connected client. Tool availability and permissions depend on the server and account configuration.