MCP 服务器

Nerq MCP Server

Provides trust scores, comparisons, and search for software entities, AI tools, packages, and MCP servers using Nerq's Trust Score system.

README

Nerq MCP Server

Official first-party MCP server for the Nerq catalog (nerq.ai).

Nerq indexes 6.8M+ software entities, AI tools, packages, and 41,368 MCP servers, each with an independent Trust Score. This Model Context Protocol server exposes Nerq's trust judgments as agent tools, so an agent can check trust before it acts.

Hosted endpoint (Streamable HTTP): https://mcp.nerq.ai/mcp
Server card: https://mcp.nerq.ai/.well-known/mcp/server-card.json
Registry namespace: ai.nerq/mcp (DNS-verified on nerq.ai)
Free, no authentication.

This is Nerq's own server for its own catalog — first-party, not a third-party wrapper. The catalog and the trust judgments are hosted; this repository is a thin client bridge and a manifest. It holds no data, no database access, and no business logic.

Install

Or point any Streamable-HTTP MCP client at https://mcp.nerq.ai/mcp (see Using it below).

Tools

Tool	Signature	Returns
`is_safe`	`is_safe(entity)`	Trust Score, grade, verdict (safe / caution / elevated risk / not yet scored), `source_url`. Abstains if the entity can't be confidently resolved.
`compare`	`compare(a, b)`	Head-to-head by Nerq Trust Score, with a winner — or `status: "cannot_compare"` if either side can't be confidently resolved. Nerq abstains rather than compare the wrong entity.
`search_assets`	`search_assets(query, type?, limit?)`	Entities matching `query`, ranked by Trust Score. Optional `type` filter (`npm`, `pypi`, `crates`, `mcp_server`, …).
`find_mcp_servers`	`find_mcp_servers(capability?, limit?)`	MCP servers matching a capability keyword, ranked by Trust Score, from Nerq's index of 41,368.

Design guarantees

Never fabricates. Resolution is exact — no fuzzy matching. On a miss the tools abstain (found: false / cannot_compare) rather than return a wrong entity: an agent acting on a fabricated match is worse than no answer.
Never a numeric zero for the unscored. An entity with no score returns "not yet scored", never 0/100.
Provenance on every response. Every result carries a source_url back to the Nerq page it came from, so the judgment is citable.

Using it

Recommended — connect directly to the hosted server (Streamable HTTP), no install:

https://mcp.nerq.ai/mcp

import asyncio
from mcp.client.streamable_http import streamablehttp_client
from mcp.client.session import ClientSession

async def main():
    async with streamablehttp_client("https://mcp.nerq.ai/mcp") as (r, w, _):
        async with ClientSession(r, w) as s:
            await s.initialize()
            print(await s.call_tool("is_safe", {"entity": "langchain"}))

asyncio.run(main())

stdio clients — this repo's server.py is a thin bridge that forwards stdio to the hosted endpoint (no data, no secrets):

pip install -r requirements.txt
python server.py            # bridges stdio -> https://mcp.nerq.ai/mcp

About Nerq

Nerq is an independent, quantitative trust layer for software and the machine economy. Trust Scores are computed from independently measured dimensions (security, maintenance, popularity, compliance, …) and are machine-readable. Learn more at nerq.ai.