Search project docs
/api/v1/search_project_docsFIND A DOCUMENTATION PAGE — start here, and this is the FIRST call for any question about these docs. Searches the project's documentation by MEANING (embeddings over a pre-built vector index), which finds the right page far more often than literal keyword matching: 'how do I reset a password' lands on a page titled 'Recovering account access', which a word search misses entirely. A LONG query is welcome, and usually better than a short one: paste the user's whole request, several questions at once included. It is split into its parts, each part searched on its own and the results merged, so a request that asks about four things returns a page for each instead of one blurred average of all four. Cheap and repeatable: the index is built once, ahead of time, so a call here is one lookup against vectors that already exist. Always answers: a project with no vector index yet is searched by full text instead, and mode ('semantic' | 'lexical') says which engine replied — no plan is required either way. Returns hits {n, title, headingPath, url, path}, best first — each with a similarity score (semantic) or a snippet (lexical); call the matching read-page tool on path for the whole page — read_project_doc on the signed-in server, the read tool this same tools/list names on the public one. Prefer search_docs only when you need a LITERAL string — an error message, a CLI flag, a regex, a file path.
Price — $0.00009 per call (twice what serving it costs us), charged to the workspace balance, the same as over MCP.
Also reachable by name at POST /api/v1/tools/search_project_docs.
Authorization: Bearer dbk_YOUR_API_KEY.Sent from your browser straight to the API — never to Docsbook, never stored.200 with ok: false: the call was made and billed, and that refusal is its answer.- Use it for any natural-language question — «где написано про…», 'where do we explain X', 'which page covers Y' — and before writing anything, so you edit the page that exists instead of adding a second one about the same thing.
- Do NOT start by listing the outline, grepping or globbing files, or opening pages one by one to look for the answer: that downloads and reads the whole site, takes many times longer and answers worse than one call here.
ok to see whether it succeeded.curl 'https://docsbook.io/api/v1/search_project_docs?query=<query>' \
-H 'Authorization: Bearer dbk_YOUR_API_KEY'{
"ok": true,
"result": "<result>",
"duration_ms": 0
}