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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.
Search official library docs and return clean text ready for LLM use.
Search local documents to ground LLM answers in your files.
Search and manage technical docs in your IDE with natural language.
Search US business entities, SEC filings, federal contracts, and lobbying data.
Turn financial documents into investment briefs with search, comparison, and risk analysis.
Retrieve technical documentation through MCP for accurate on-demand LLM references.