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Search financial docs semantically, answer with grounding, and catch CI regressions.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "findocs-mcp" yet — see the docs or source repo.
Search the connected financial document corpus for passages most relevant to 'changes in revenue recognition policy', then answer: Did the company adjust its revenue recognition method this period? Include source citations.
Relevant passages, a cited conclusion, and a concise evidence-grounded answer.
Run evaluation on this financial Q&A benchmark, checking retrieval recall and answer faithfulness; if there is regression versus baseline, mark the run as failed and output a diff report.
Evaluation results, regression verdicts, and failure reasons to catch quality issues before release.
Configure a CI regression gate for a financial document retrieval and Q&A service: run evaluations on every commit, block merges if retrieval quality or answer faithfulness drops, and produce a summary report.
An automated CI-integrated check flow and a clear summary of quality gate outcomes.
Provide AI coding assistants with up-to-date enterprise and developer documentation.
Search multiple documentation sites semantically to find technical information faster.
Search local documents to ground LLM answers in your files.
Local-first MCP server for web search and developer documentation fetching.
Search and retrieve files from a local docs folder quickly.
Search and manage technical docs in your IDE with natural language.