skillfed-mcp — optional Node MCP server

Find vetted agent skills for your task — exposes the Skill Federation finder to Claude and any MCP client as first-class MCP tools (find_skills, get_skill_bundle).

This is the optional Node tier. The default Skill Federation install is the runtime-free curl-based plugin under ../integrations/claude-code/ — it needs no Python and no Node and works on the standalone Claude Code desktop build. Use this Node server only if you're on the npm Claude Code CLI (or otherwise have Node ≥18) and want Claude to call the federation as first-class MCP tools (no shell-out).

It exposes the same hosted federation as four MCP tools over stdio:

| Tool | Maps to | Purpose | |---|---|---| | find_skills | /search (per wish, fanned out) | lexical-recall search over a wish-list | | get_skill_bundle | /fetch | fetch a confirmed match's files for install | | report_selection | /report_selection | per-wish selection label; chosen = id, or the literal "None" if all rejected | | emit_demand_pointer | /report_demand | demand on a miss (empty OR all-rejected): wish + a sketch string per demand-sketch.md |

The request/response shapes are identical to the curl plugin's /search, /fetch, /report_selection, and /report_demand calls. Note the endpoint requires a non-empty chosen (use "None") and a non-empty wish, and sketch is a string, not an object.

Requirements

• Node ≥18 (global fetch + stable fs). Not present on the standalone Claude Code desktop build — check with node --version.

Register it

Add to your project .mcp.json (or ~/.claude.json). The server installs nothing for you — npx fetches and caches it on first use.

Release (published to npm):

{
  "mcpServers": {
    "skillfed-mcp": {
      "command": "npx",
      "args": ["-y", "skillfed-mcp"],
      "env": { "SKILLFED_ENDPOINT": "https://qurini-skill-federation.hf.space" }
    }
  }
}

Local dev (from this repo): npm install here once (for @modelcontextprotocol/sdk), then

{
  "mcpServers": {
    "skillfed-mcp": {
      "command": "node",
      "args": ["<abs path>/mcp-server/index.mjs"],
      "env": { "SKILLFED_ENDPOINT": "https://qurini-skill-federation.hf.space" }
    }
  }
}

Config (env)

| Var | Default | Meaning | |---|---|---| | SKILLFED_ENDPOINT | (required) | hosted federation URL | | SKILLFED_API_KEY | (none) | bearer token (qurini demo is keyless) | | SKILLFED_TENANT | $USER/$USERNAME/local | tenant id | | SKILLFED_TOP_N | 5 | candidates per wish | | SKILLFED_K | 4 | paraphrase formulations concatenated per query |

Test without Claude

npm install
npx @modelcontextprotocol/inspector node index.mjs
# then call find_skills with ../integrations/sample_wishlist.json