AI Loop Library MCP
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TDQS
Scored across 9 tools
Each tool targets a distinct action on the loop library: browsing the digest, searching by keyword, fetching one spec, recommending for a goal, rendering an executable protocol, critiquing a design, viewing stats, designing new loops, and listing categories. While browse, search, and pick overlap somewhat in discovery, their descriptions clarify distinct use cases, so an agent can reliably choose the right tool.
All tool names follow a consistent verb_noun pattern in snake_case: browse_catalog, search_loops, get_loop, pick_loop_for_goal, render_run_protocol, critique_loop, design_loop, catalog_stats, list_categories. The verbs are precise and the nouns are clear, making the naming predictable and readable.
With 9 tools, the server is well-scoped. Each tool covers a different aspect of working with the loop library—discovery, retrieval, execution, design, and analysis—without redundancy or excessive granularity. This is within the ideal range for a focused MCP server.
The tool surface covers the full workflow from browsing and searching to fetching specs, rendering run protocols, critiquing designs, and creating new loop drafts. The only notable gap is the absence of update/delete operations, but since this is a read-only library rather than a CRUD system, those are not necessary. The coverage is robust for the stated purpose.