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mcp-name: io.github.CSOAI-ORG/mcp-scorecard-mcp

MCP Scorecard: 18/100

mcp-scorecard-mcp

Score any MCP server against a 100-point production-readiness rubric — static (AST + filesystem), PyPI health, and directory-presence signals. The engine is stdlib-only (no deps to score).

Rubric (10 categories, 100 pts)

readme · tool design (names + descriptions) · examples · tests/CI · transports (stdio/http) · metadata (server.json, license) · reliability (importable, versioned) · security · docs surface · provenance (PAYG/Stripe/attestation, directory listings).

Use

# score one package dir
python -c "from mcp_scorecard import collect_static, score, score_to_row; \
  import json; print(json.dumps(score_to_row(score(collect_static('.'))), indent=2))"

# batch-score a whole marketplace tree → leaderboard JSON + CSV
python -m mcp_scorecard.runner --root ./mcp-marketplace --out ./scoreboard --no-network
# (drop --no-network to fold in live PyPI download stats)

Why

A buyer's-eye quality signal for the MCP explosion: is a server actually production-ready, or a stub? Powers the MEOK lead-magnet scorecard and our own flagship-tier triage.

Live example (MEOK marketplace, 2026-06-07, static-only)

338 packages scored · mean 62.9/100 · 110 flagship-grade. Top: iso-27001-ai-mcp (84), proofof-ai-mcp (79), eu-ai-act-compliance-mcp (78).

Optional: run as an MCP server

pip install "mcp-scorecard-mcp[server]" then run the score_mcp tool (see server.py).


Part of the MEOK constellation

This MCP is one node in a connected ecosystem built by MEOK AI LABS around a single sovereign AI core — governed agents with a hash-chained audit trail, mapped to the CSOAI compliance charter.

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