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DecimalAI Skills Registry

Search agent skills ranked by measured lift vs a no-skill baseline, with safety and rankings.

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README

From the repo.

decimalai-mcp

Part of DecimalAI. Most users want the Python SDK → decimal-labs/decimalai-python.

MCP server for the DecimalAI skills registry — the registry that ranks agent skills by measured effectiveness (verified A/B benchmarks, live pass rates, AI rater scores), not download counts.

PyPI Downloads CI Python License

Gives any MCP client (Claude Desktop, Claude Code, Cursor, …) three read-only tools:

ToolWhat it does
search_skills(query, category?, sort?, limit?)Hybrid keyword/semantic search over the public registry
get_skill(slug)Full record: trust & safety-scan status, verified benchmark lift, SkillScore, ratings, SKILL.md body
get_leaderboard(sort?, category?, window_days?, limit?)Ranked leaderboard: skill_score, biggest_improvement, efficiency, top_rated

No API key required — all three tools read public registry endpoints. If you set DECIMAL_API_KEY (from app.decimal.ai/settings), the same tools additionally show which skills your org has already installed (installed_as).

Install

pip install decimalai-mcp
# or, no install needed at config time:
uvx decimalai-mcp

Requires Python 3.10+.

Claude Code

claude mcp add decimalai -- uvx decimalai-mcp
# with an API key:
claude mcp add decimalai -e DECIMAL_API_KEY=dai_sk_... -- uvx decimalai-mcp

Claude Desktop

Add to claude_desktop_config.json (Settings → Developer → Edit Config):

{
  "mcpServers": {
    "decimalai": {
      "command": "uvx",
      "args": ["decimalai-mcp"],
      "env": {
        "DECIMAL_API_KEY": "dai_sk_optional"
      }
    }
  }
}

Omit the env block entirely for anonymous read-only access.

Configuration

Env varDefaultPurpose
DECIMAL_API_KEY(unset)Optional. Unlocks per-org enrichment (e.g. installed_as) on the same public endpoints.
DECIMAL_API_URLhttps://api.decimal.aiPoint at a self-hosted / local backend.

Why no check_manifest_impact tool?

The manifest-impact endpoint (POST /api/v1/regression-check) is authenticated on the platform — it analyzes your org's production traces against a candidate manifest, so there is no public variant to expose. This server is deliberately a read-only, key-optional public-registry surface. If demand shows up, an authed check_manifest_impact (requiring DECIMAL_API_KEY) is a natural v0.2 addition; the regression-check GitHub Action covers the CI use-case today.

Endpoints used (all public)

  • GET /api/v1/registry/skills — browse/search
  • GET /api/v1/registry/skills/{slug} — detail
  • GET /api/v1/registry/leaderboard — ranked leaderboard (category filtering falls back to the browse endpoint's documented view=ranks mode, because the leaderboard endpoint is uncategorized)

Development

pip install -e ".[dev]"
pytest              # all HTTP mocked; no network
python -m decimalai_mcp.server   # run over stdio

Run pytest yourself before opening a PR. CI also asserts that the pinned mcp<2 still provides FastMCP, which the mocked tests do not cover — run that one too:

python -c "from mcp.server.fastmcp import FastMCP; import decimalai_mcp.server"

Releases are cut from a published GitHub Release — see RELEASING.md for the gates a change has to pass and the version strings that must move together.

License

MIT

Config for your environment

Replace {MCP_ENDPOINT_URL} with this MCP’s endpoint URL (from its repo or docs above). No API key — you connect directly.

Tool

OS

Config file: ~/.cursor/mcp.json

{
  "mcpServers": {
    "mcp-server": {
      "url": "{MCP_ENDPOINT_URL}"
    }
  }
}

Paste into mcpServers in the config file. Restart Cursor after saving.

If this MCP is also published on mcpchannel.ai, you can subscribe from Browse and use the gateway config there instead.