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Index local SQLite, CSV, and Markdown metadata for hybrid semantic search.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "mcp-ready-data-discovery-tool" yet — see the docs or source repo.
List available sources, then index /data/sales.db, /docs/specs.md, and /files/customers.csv, and return the indexing status for each source.
A list of available sources, indexing results, and status or error details for each source.
Search indexed data for "customer churn reasons" and "renewal risk" using both keyword and semantic matching, return the top 10 results by relevance, and include the source file or table name.
Ranked matches with snippets, relevance scores, and the corresponding source locations.
Get the schema for the orders table in sales.db, then summarize key fields, field types, and useful directions for further analysis.
Detailed table schema plus a concise explanation of important fields and analysis opportunities.
Search local documents by keyword, fetch passages, and list sources offline.
Search a personal document collection semantically and retrieve full source documents.
Index documents offline in SQLite and query them with hybrid natural-language search.
Run hybrid search over self-hosted public data indexes via MCP.
Research, classify, score, and forecast every row in a dataset
Enable MCP agents to discover data, match schemas, and export via HTTP.