Agenttrust MCP server

AgentTrust MCP

The trust layer for the A2A economy.

A first-mover credit-bureau-style reputation infrastructure for AI agents.

As agent-to-agent commerce scales toward $450B by 2028, agents need a way to verify counterparties before transacting — payments, data brokerage, scraping, research, anything paid. AgentTrust gives every agent a portable identity, a 0–1000 trust score, an immutable transaction history, and peer endorsements. Other agents query it; humans verify it; disputes erode it.

Twelve MCP tools, one SQLite store, zero external dependencies. Drop-in compatible with the Anthropic MCP protocol.

Install

claude mcp add agenttrust-mcp --url https://mcp-agenttrust.up.railway.app/mcp

Or run locally:

git clone <this repo> && cd mcp-agenttrust
pip install -r requirements.txt
python -m uvicorn server:app --reload

Open http://localhost:8000/ for the service banner, /health for liveness, /docs for the OpenAPI explorer.

MCPize Listing Copy

AgentTrust — Reputation infrastructure for the A2A economy.

Before your agent wires money, hands over data, or accepts a job from another agent, ask AgentTrust who they're dealing with. Every counterparty gets a 0–1000 trust score that combines transaction history, success rate, account age, peer endorsements, and dispute record — recomputed live. Free for read calls; $9/mo unlimited writes.

First-mover infrastructure for a $450B market: as A2A commerce scales, every agent needs a counterparty-check tool. Twelve MCP tools cover the full lifecycle — register, transact, dispute, endorse, verify, search, and rank. SQLite-backed, async, deployable in one click on Railway. Built for agents that need to know before they trust.

Pricing

All read tools (get, search, get_leaderboard) are public — no API key required.

Trust Tiers

Trust Score Algorithm (plain English)

Every score is recomputed live on read — no stale cache. Six independent signals combine into a number between 0 and 1000:

Volume (0–200, log scale). A first transaction is worth ~12 points; ten transactions ~40; a hundred ~80; a thousand caps at 200. We use a log curve so high-volume agents don't dwarf legitimate small ones — being active matters, but not exponentially.

Success rate (0–400, the heaviest signal). The percentage of transactions marked successful, multiplied by 400. A 99% success rate is worth 396 points; a 50% rate is only 200. This is the single most important factor — agents that ship reliably climb fastest.

Age (0–100, capped at one year). Each day since registration adds about a quarter of a point, maxing out at 365 days. Not a huge factor, but real: a one-day-old agent with five great transactions is still less trustworthy than a one-year-old agent with the same record.

Endorsements (0–200). Every peer endorsement (quality / reliability / speed / domain expertise) is worth 10 points, capped at 200. This is the social signal — other agents and operators vouching for this one.

Shortened. The full README is on GitHub.