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Turn natural language questions into SQL and run them on SQLite databases.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Text2SQL MCP Server" yet — see the docs or source repo.
Convert this question to SQL and execute it: What are the top 10 best-selling products in the last 30 days? Return the result as a table.
It generates the SQL and returns a table with the top 10 products.
Answer using the SQLite database: What is the current total number of users? Return a short string result if appropriate.
It creates a counting SQL query and returns a single value or short text result.
Convert the following question to SQL and execute it: Count orders for each month this year, sorted by time ascending.
It generates a monthly aggregation query and returns a time-ordered result table.
Data analysts or developers can ask questions in natural language instead of writing SQL manually and get database results back. It is useful for quick statistics, filtering, and aggregation.
Researchers or product managers can turn business questions directly into SQL and run them against a SQLite database to validate data-driven conclusions. The output can be returned as a table or a string for easy reading.
It converts natural language questions into SQL and executes them against SQLite databases. Results are returned as tables or strings.
The provided information only explicitly mentions SQLite databases. For support of other databases, see the source repository.
The current materials do not provide installation or configuration steps. For prerequisites, runtime details, and parameters, see the source repository.
Query SQL databases in natural language with auto-generated, self-correcting SQL.
Query and manage SQLite databases using natural language through an MCP tool.
Safely explore and query SQLite databases using natural language.
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Convert plain English into SQL and interactively inspect and query databases.
Query any SQL database in natural language with safe auto-generated SQL.