An MCP server for discovering, ranking, and retrieving agent skills while minimizing context usage.
MCP server that ranks and retrieves agent skills, so an agent loads the smallest sufficient context instead of an entire catalog.
Skill Router is an MCP server that indexes the SKILL.md catalogs already present on a machine, ranks them against a described task, and returns a short list of candidates with the reason each one was selected. It speaks stdio to any MCP client — Claude Code, Codex, OpenCode — and ships as a self-contained binary per platform.
Ranking is deterministic: no model call, no network, no embedding index. The same query against the same catalog always returns the same list in the same order, which is what makes the routing decision reproducible and testable.
Coding agents already discover and select skills on their own, and that works while the catalog is small and each skill is clearly different from the rest.
It stops working as the catalog grows. With a hundred skills the agent has to read a hundred descriptions, tell overlapping ones apart, and decide what is relevant before starting the actual task. Progressive disclosure limits how much of each skill is exposed, but the routing decision still happens inside the agent's context, competing for attention with the work.
Skill Router moves that decision into a retrieval layer. The agent describes the task instead of reading the catalog:
and gets back a ranked shortlist, each entry carrying the signals that put it there:
From the project README.
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