* feat(mcp): add search_docs tool over Mintlify docs corpus
Closes#295. The docs at https://docs.dograh.com promise "Search the
Dograh docs for how to configure a TURN server" as an MCP example
prompt, but no search_docs tool exists in the MCP server — agents can
list workspace resources but cannot search the documentation.
This adds a dependency-free, in-process keyword search over the
`docs/` tree shipped into the API image (`COPY ./docs ./docs`):
- New `api/mcp_server/tools/docs_search.py` — async `search_docs(query,
limit=10)` with weighted scoring (path > title > body), a 25-result
hard cap, snippet extraction around the first term hit, and graceful
empty-list degradation when docs aren't on disk. `DOGRAH_DOCS_PATH`
env var overrides location discovery for non-Docker layouts.
- Registered in `api/mcp_server/server.py` alongside the other tools,
keeping the existing list-alphabetical convention.
- `api/tests/test_mcp_docs_search.py` — 18 unit tests covering the
pure helpers (tokenizer, frontmatter stripping, title extraction,
scoring weights, URL building) and end-to-end ranking, limit
clamping, empty-corpus degradation, and input-validation errors.
Mocks `authenticate_mcp_request` to avoid the DB dependency,
mirroring `test_mcp_save_workflow.py`.
Implementation notes:
- The docs corpus is ~100 files / ~140k LoC, so a per-call scan runs
well under 50 ms; avoiding a vector index / embedding backend keeps
the tool zero-dependency and works for fully offline self-hosted
deployments.
- Authentication is required for consistency with the other MCP tools
(and to route through the existing rate-limit middleware), even
though docs are not org-scoped data.
- Title/path matches deliberately outweigh body matches so a page
whose subject IS the query term outranks one that merely mentions
it incidentally.
* feat: improve docs search
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Co-authored-by: Abhishek Kumar <abhishek@a6k.me>
