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Query PostgreSQL in natural language with error recovery, audit trace, and result checks.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Interactive Database Analyst via MCP" yet — see the docs or source repo.
Connect to my PostgreSQL database and, based on the existing schema, find the top 10 products by sales in the last 90 days. Also explain which tables and fields you used; if the query fails, automatically fix it and retry.
Returns the query results, the schema grounding used, and an explanation of any error correction and retry steps.
Please query the number of new paying users in Q1 2024. If the result is empty, perform an empty-result sanity check and break the task into smaller exploratory queries to help identify the cause.
Outputs the main query result and, if empty, provides decomposed exploratory queries and likely causes.
Help me count orders by region for the last 30 days, and show the full live audit trace, including your query steps, correction process, and how you verified the results.
Provides the aggregated results along with a traceable record of execution and validation.
Data analysts or product managers can ask questions against a PostgreSQL database in natural language without writing SQL first. The tool uses schema grounding to interpret the request and return results.
When a generated database query fails, this tool attempts self-correction and retries. This reduces the time spent manually debugging SQL syntax or field reference issues.
In situations where a traceable analysis process is important, users can review a live audit trail. For empty results, exploratory decomposition and sanity checks help assess whether the outcome is trustworthy.
It is used to query PostgreSQL databases in natural language. It also supports schema-grounded understanding, self-correcting recovery, a live audit trace, and exploratory result verification including empty-result checks.
The provided information only explicitly mentions PostgreSQL. For support of other databases, see the source repository.
The current materials do not provide installation steps or runtime prerequisites. At minimum, it would typically involve PostgreSQL connection access; for details, see the source repository.
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