AgentTrust — Pre-Invocation AI Agent Trust & Reliability Checks
RemoteAbout AgentTrust — Pre-Invocation AI Agent Trust & Reliability Checks
AgentTrust provides read-only checks of AI agent and MCP server endpoints before invocation, for systems deciding whether to interact with them. It returns observed reliability evidence, endpoint-ownership verification, and a machine-readable trust decision without contacting the checked endpoint.
Key features
- 01Pre-invocation endpoint checks
- 02Observed reliability evidence
- 03Endpoint ownership verification
- 04Machine-readable trust decision
- 05No account or API key for public checks
Use cases
- 01Check an agent endpoint before calling it
- 02Review reliability signals before interaction
- 03Add a trust check to an agent workflow
MCP support
Its public Streamable HTTP MCP endpoint provides the read-only `check_agent_trust` and `assess_agent` tools. An authenticated management MCP server also exposes agent records, health checks, and heartbeats.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://getagenttrust.com/api/mcp/publicclaude mcp add --transport http agenttrust-ai-agenttrust https://getagenttrust.com/api/mcp/public{"mcpServers":{"agenttrust-ai-agenttrust":{"type":"http","url":"https://getagenttrust.com/api/mcp/public"}}}Open in Cursor{"servers":{"agenttrust-ai-agenttrust":{"type":"http","url":"https://getagenttrust.com/api/mcp/public"}}}Open in VS Code{"mcpServers":{"agenttrust-ai-agenttrust":{"type":"http","url":"https://getagenttrust.com/api/mcp/public"}}}{"mcpServers":{"agenttrust-ai-agenttrust":{"serverUrl":"https://getagenttrust.com/api/mcp/public"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
https://getagenttrust.com/api/mcp/publichttps://getagenttrust.com/api/mcpAuth requiredTools
1| Parameter | Type | Required | Description |
|---|---|---|---|
| endpointUrl | string | Yes | The exact invocation URL of the agent you're about to call. Used only to look up AgentTrust's own already-observed data for it — this endpoint is never contacted during the check. |
Details
From the project READMEAgentTrust — Pre-invocation Trust Check for AI Agent Endpoints
Check an AI agent or MCP server endpoint before you call it. Given the exact
endpoint URL, AgentTrust returns the reliability evidence it has already
collected, endpoint-ownership verification, and a machine-readable
trustDecision — without contacting the endpoint.
No AgentTrust account or API key required · Read-only · MCP and TypeScript SDK
AgentTrust is trust infrastructure for AI agents. It provides
reliability monitoring, endpoint verification, and pre-invocation trust
checks for MCP and A2A agents. An agent registers an identity, gets
continuously health-monitored, optionally proves ownership of its
endpoint, and accumulates a deterministic reliability score from that
observed history. Any external AI agent or system can look up another
agent by its invocation URL and get back a machine-readable
trustDecision — a signal derived from AgentTrust's own observed and
verified data, for the caller to weigh, never a certification or
guarantee of safety — before deciding whether to interact with it.
Official MCP Registry identity: io.github.agenttrust-ai/agenttrust.
Quick start — no account needed
Every example below checks AgentTrust's own monitored test agent,
https://agenttrust-umber.vercel.app/api/test-agent; swap in the URL you're
about to call.
MCP
Add the public connector https://getagenttrust.com/api/mcp/public
(Streamable HTTP, no authentication; two read-only tools, check_agent_trust
and assess_agent).
In Claude Code:
claude mcp add --transport http agenttrust https://getagenttrust.com/api/mcp/public
Claude Desktop, Cursor and a plain curl call:
Connect an MCP client.
TypeScript SDK
npm install @getagenttrust/sdk
import { checkAgentTrust } from "@getagenttrust/sdk";
// AgentTrust's own test agent: a real, monitored endpoint you can check.
const result = await checkAgentTrust("https://agenttrust-umber.vercel.app/api/test-agent");
if (result.matched) {
console.log(result.status, result.reliabilityScore, result.trustDecision);
// e.g. "healthy" 100 { recommended: true, confidence: "high", reasons: [] }
} else {
// AgentTrust has no data for this endpoint (yet). An unmatched result never
// carries a score; result.observation may say it was queued for a lookup.
console.log("Unknown endpoint", result.observation?.status);
}
Policies (assertTrusted), errors and options: SDK README
· npm.
In the browser
Check the test agent on getagenttrust.com.
Public checks vs. agent management
| Public trust checks | Agent management | |
|---|---|---|
| For | Checking any endpoint before you call it | Registering and monitoring your own agents; full agent records |
| Account / API key | Not needed | Account and API key (Authorization: Bearer <API_KEY>) |
| Interfaces | MCP check_agent_trust at /api/mcp/public; @getagenttrust/sdk | REST /api/v1/*; MCP server /api/mcp (list_agents, get_agent, get_agent_health, send_heartbeat) |
To register an agent: sign up, create a key under Dashboard → API keys, then follow Getting started (REST).
Documentation
You don't need this repository to use AgentTrust:
- /docs — full REST, MCP and SDK reference.
- /llms.txt — the same reference as one plain-text file, for an LLM's context.
Developing this project
This is a Next.js (App Router) + Drizzle + Supabase app, deployed on Vercel.
npm install
npm run dev
Open http://localhost:3000. You'll need a
.env.local — see .env.example for the required variables (Supabase
credentials, database connection strings, and the server-only secrets
described inline).
Useful scripts:
npm run test # vitest — full suite runs against an embedded pglite DB, no live database needed
npm run typecheck # tsc --noEmit
npm run lint # eslint
npm run db:generate # generate a new Drizzle migration from schema changes (offline)
npm run db:migrate # apply pending migrations to the database in DIRECT_URL
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.