AgentTrust

Name: AgentTrust
Author: assister-xyz

by assister-xyzversion 0.1.2i★ –iRuns on your computer

Registry nameio.github.assister-xyz/agenttrust

Install

Overview

Description from the maker (original English)

Quality verification for AI agents and MCP servers. 6-axis scoring, adversarial probes.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiVery new↓ 33/wk · ★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Other
You need to fill in: GROQ_API_KEY, CEREBRAS_API_KEY, MONGODB_URL

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: GROQ_API_KEY, CEREBRAS_API_KEY, MONGODB_URL

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "agenttrust": {
      "command": "uvx",
      "args": [
        "mcp-agenttrust"
      ],
      "env": {
        "GROQ_API_KEY": "your-value",
        "CEREBRAS_API_KEY": "your-value",
        "MONGODB_URL": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add agenttrust --env GROQ_API_KEY=your-value --env CEREBRAS_API_KEY=your-value --env MONGODB_URL=your-value -- uvx mcp-agenttrust

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "agenttrust": {
      "command": "uvx",
      "args": [
        "mcp-agenttrust"
      ],
      "env": {
        "GROQ_API_KEY": "your-value",
        "CEREBRAS_API_KEY": "your-value",
        "MONGODB_URL": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "agenttrust": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "mcp-agenttrust"
      ],
      "env": {
        "GROQ_API_KEY": "your-value",
        "CEREBRAS_API_KEY": "your-value",
        "MONGODB_URL": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

GROQ_API_KEY secret env
Groq API key for LLM judge (free tier available at console.groq.com)
CEREBRAS_API_KEY secret env
Cerebras API key for LLM judge (free tier available at cloud.cerebras.ai)
MONGODB_URL secret env
MongoDB connection URL for persistent storage

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 9, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account assister-xyz, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

More stars than 0% of the other 18654 servers in this category
Published to the registry more recently than 3% of the other 18654 servers in this category
Basic checks equal to or better than 100% of the other 18654 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is AgentTrust safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: GROQ_API_KEY, CEREBRAS_API_KEY, MONGODB_URL

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.2) reached the registry 8 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Show HN Launches — buy per-query in-session (showhnwatch)

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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Install

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Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

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Install

Show HN Launches — buy per-query in-session (showhnwatch)

Show HN: indie launches & side projects. $0.01/query. Be born in one call — free testnet funds.

by ee324EarlyUpdated today

Runs in the cloud✓ a2awire.com

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

AgentTrust

Challenge-response quality verification for AI agents and MCP servers.

AgentTrust evaluates AI agent competency *before* you trust them with real tasks or payments. It connects to any MCP server, runs challenge-response tests across 6 quality dimensions, and issues W3C Verifiable Credentials as proof.

Why

The AI agent ecosystem has identity (ERC-8004, SATI), post-hoc reputation (TARS, Amiko), and payments (x402) — but no pre-payment quality gate. AgentTrust fills this gap: verify competency first, then trust.

Features

Evaluation Engine

3-level pipeline: Manifest (schema) → Functional (tool calls) → Domain Expert (calibrated questions)
6-axis scoring: accuracy (35%), safety (20%), reliability (15%), process quality (10%), latency (10%), schema quality (10%)
Consensus judging: 2-3 LLM judges in parallel with agreement threshold (saves 50-66% LLM calls)
7 LLM provider fallback chain: Cerebras → Groq → OpenRouter → Gemini → Mistral → DeepSeek → OpenAI
5 adversarial probe types: prompt injection, PII leakage, hallucination, overflow, system prompt extraction

Battle Arena

Head-to-head blind evaluation with position-swap consistency
OpenSkill (Bayesian ELO) rating system with divisions (Bronze → Grandmaster)
Fair matchmaking: rating proximity + uncertainty bonus + cross-division challenges
Style control penalties to prevent gaming via verbose/formatted responses

IRT Adaptive Testing

Rasch 1PL calibration from battle data (pure Python, no numpy)
Fisher information maximization for adaptive question selection
EAP ability estimation with standard normal prior
Reduces evaluation cost by 50-90% while maintaining accuracy

Standards

W3C Verifiable Credentials (AQVC format) with Ed25519 DataIntegrityProof
Google A2A v0.3 native support (AgentTrust IS an A2A agent)
x402 Solana payment verification (USDC + SOL)
AIUC-1 protocol mapping

Quick Start

Docker (recommended)

cp .env.example .env

Add at least one LLM key (GROQ_API_KEY, CEREBRAS_API_KEY, etc.)

docker compose up -d

Services:

API: http://localhost:8002
MCP Server: http://localhost:8003
Health: http://localhost:8002/health

Local Development

python -m venv .venv && source .venv/bin/activate

pip install -r requirements.txt cp .env.example .env

Add LLM keys to .env

unset GROQ_API_KEY # Shell env overrides .env rotation pool python -m uvicorn src.main:app --host 0.0.0.0 --port 8002 --reload

MCP Server (for Claude, Cursor, Windsurf)

Add to your MCP client config:

"mcpServers": { "agenttrust": { "command": "python", "args": ["-m", "src.standards.mcp_server"], "env": { "GROQ_API_KEY": "your-key" } } } }

Or connect to a running instance via SSE:

http://localhost:8003/sse

Available MCP tools:

Tool	Description
`check_quality(server_url)`	Full evaluation: manifest + functional + judge scoring
`check_quality_fast(server_url)`	Cached score (<10ms) or manifest-only (<100ms)
`get_score(server_url)`	Lookup cached score with freshness decay
`verify_attestation(attestation_jwt)`	Verify AQVC JWT and decode payload

API Endpoints

Method	Endpoint	Description
POST	`/v1/evaluate`	Submit target for evaluation
GET	`/v1/evaluate/{id}`	Poll evaluation status
GET	`/v1/score/{target_id}`	Get quality score
GET	`/v1/scores`	Search/list scores
GET	`/v1/badge/{target_id}.svg`	SVG quality badge
GET	`/v1/attestation/{id}`	Get signed attestation (JWT or W3C VC)
POST	`/v1/attestation/{id}/verify`	Verify attestation
POST	`/v1/feedback`	Submit production feedback (anti-sandbagging)
POST	`/v1/battles`	Create evaluation battle
GET	`/v1/arena/leaderboard`	Battle arena leaderboard
GET	`/v1/rankings`	Global rankings by domain/tier
POST	`/v1/irt/calibrate`	Trigger IRT batch calibration
GET	`/v1/irt/recommend`	Adaptive question selection
GET	`/v1/pricing`	x402 pricing table
GET	`/.well-known/agent.json`	A2A Agent Card

Architecture

src/

api/v1/ # 14 FastAPI routers core/ # Evaluator, MCP client, scoring, IRT, battle arena auth/ # API keys (SHA256 + salt), rate limiting by tier storage/ # MongoDB (Motor) + Redis payments/ # x402 protocol, Solana verification standards/ # W3C VC issuer, A2A extension, MCP server, AIUC-1

Stack: FastAPI + MongoDB + Redis | 533 tests | 60 source files | 15 lean dependencies

Tests

python -m pytest tests/ -q

533 passed in ~2s

Configuration

See .env.example for all 60+ configuration options including:

LLM API keys (7 providers, comma-separated for rotation)
MongoDB/Redis connection
JWT attestation (Ed25519 key, issuer DID, validity)
Solana wallet for x402 payments
Rate limit tiers and consensus judge settings

License

MIT

AgentTrust

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

Show HN Launches — buy per-query in-session (showhnwatch)

README from the maker

AgentTrust

Why

Features

Quick Start

Docker (recommended)

Add at least one LLM key (GROQ_API_KEY, CEREBRAS_API_KEY, etc.)

Local Development

Add LLM keys to .env

MCP Server (for Claude, Cursor, Windsurf)

API Endpoints

Architecture

Tests

533 passed in ~2s

Configuration

License

Links