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Problem Statement

Agent Skills support in AI applications demonstrates demand for rich workflow instructions, but there's no convention for exposing equivalent functionality through MCP primitives.

Current Limitations

  • Server instructions load only at initialization — new or updated skills require re-initializing the server
  • Complex workflows exceed practical instruction size — some skills require hundreds of lines of markdown with references to bundled files, scripts, and examples
  • No discovery mechanism — users installing MCP servers from a registry don't know if there's a corresponding skill they should also install
  • Multi-server orchestration — skills may need to coordinate tools from multiple servers, which doesn't fit the single-server instruction model

Broader Context

Skills discoverability is a specific instance of a more general MCP challenge: context-as-resources discoverability and standardization of client host behavior around non-tool primitives. The ecosystem has largely optimized for tools, and patterns for how clients discover and consume other forms of context — including skills — remain underdeveloped. Solutions in this space are likely to have implications beyond skills alone.

MCP's value for skills goes beyond distribution; it provides an interaction model. MCP defines app, human, and assistant roles, giving skills a built-in framework for control model decisions (who sees the content, who decides when it loads). This makes MCP a natural complement to skills as a delivery channel for workflow instructions.

Key Use Cases

See use-cases.md for detailed use cases and community input. In summary:

  1. Complex Workflow Orchestration — Multi-step workflows requiring 875+ lines of instruction (e.g., mcpGraph)
  2. Conditional Workflows — Branching instructions dynamically loaded based on context
  3. Multi-Server Composition — Skills leveraging tools from multiple off-the-shelf servers
  4. Progressive Disclosure — Skills broken into linked file sets, loaded on demand

Open Questions

See open-questions.md for the full list of unresolved questions with community input.

For the value proposition and a guide on when MCP distribution applies, see why-and-when.md.