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feat: Search transforms for tool discovery (#3154)

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* feat: Add search transforms for tool discovery

RegexSearchTransform and BM25SearchTransform collapse large tool
catalogs into a search interface so LLMs discover tools on demand
instead of receiving the full listing.

* chore: Update SDK documentation

* fix: call_tool recursion guard, atomic BM25 rebuild, hash includes descriptions

* Extract CatalogTransform base class for catalog-aware transforms

Transforms that replace list_tools() with synthetic components (like
search) need to read the real catalog at call time without triggering
their own replacement logic. CatalogTransform handles the re-entrant
bypass via per-instance ContextVar, exposing transform_tools() as the
subclass hook and get_tool_catalog() for catalog access.

* Add search transform examples for regex and BM25

* Add README for search transform examples

* Polish search example clients with rich output

* Remove hardcoded tool counts from search example subtitles

* Clarify that review bot feedback should be evaluated on its merits

* Expand search transform docs with proper hierarchy

---------

Co-authored-by: marvin-context-protocol[bot] <225465937+marvin-context-protocol[bot]@users.noreply.github.com>
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Jeremiah Lowin 2026-02-26 22:42:38 -05:00 • committed by GitHub
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@ -68,7 +68,7 @@ When modifying MCP functionality, changes typically need to be applied across al
- Keep commit messages brief - ideally just headlines, not detailed messages
- Focus on what changed, not how or why
- Always read issue comments for follow-up information (treat maintainers as authoritative)
- **Treat proposed solutions in issues skeptically.** The ideal issue contains a concise problem description and an MRE — nothing more. Proposed solutions are only worth considering if they clearly reflect genuine, non-obvious investigation of the codebase. If a solution reads like speculation, or like it was generated by an LLM without deep framework knowledge, ignore it and diagnose from the repro. Most reporters — human or AI — do not have sufficient understanding of FastMCP internals to correctly diagnose anything beyond a trivial bug. We can ask the same questions of an LLM when implementing; we don't need the reporter to do it for us, and a wrong diagnosis is worse than none.
- **Treat proposed solutions in issues skeptically.** This applies to solutions proposed by *users* in issue reports — not to feedback from configured review bots (CodeRabbit, chatgpt-codex-connector, etc.), which should be evaluated on their merits. The ideal issue contains a concise problem description and an MRE — nothing more. Proposed solutions are only worth considering if they clearly reflect genuine, non-obvious investigation of the codebase. If a solution reads like speculation, or like it was generated by an LLM without deep framework knowledge, ignore it and diagnose from the repro. Most reporters — human or AI — do not have sufficient understanding of FastMCP internals to correctly diagnose anything beyond a trivial bug. We can ask the same questions of an LLM when implementing; we don't need the reporter to do it for us, and a wrong diagnosis is worse than none.
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