skills-mcp

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The Problem

AI agents have broad knowledge, but narrow expertise.

The agent isn’t making mistakes from lack of knowledge — it’s missing the procedural playbook. It’s like having a senior engineer who’s never seen your company’s runbooks.

Agent Skills solve the playbook problem, but they normally live as files on a single machine or inside one tool’s plugin — so every new tool, repo, and teammate keeps its own copy, and there’s no shared, always-available library your agents can consult on demand.

What if one registry could serve them all?

The Solution: the Agent Skills model, as a shared service

skills-mcp takes the Agent Skills model and makes it a shared, searchable service. The same expert procedures, domain best practices, verified patterns, and reference material you’d put in SKILL.md files live in one registry that agents discover and load at the moment they need them, over MCP — no per-tool file syncing, no dumping every skill into context.

You:   "Add Stripe subscriptions with webhook verification"

Agent: → calls skills_find_relevant("Stripe subscriptions webhooks")
         Returns: stripe-integration (confidence: 0.89)

       → calls skills_get_body("stripe-integration")
         Gets: API patterns, webhook signing verification, 
               idempotency key handling, security checklist, 
               live launch steps

       → Executes correctly. First time. Every time.

The agent doesn’t improvise. It retrieves a versioned, authoritative playbook — the way a senior engineer pulls up the deployment runbook when something matters.