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cpenniman12

text2sql-mcp

by cpenniman12
README.md
# text2sql-mcp

<!-- mcp-name: io.github.cpenniman12/text2sql-mcp -->

MCP server for [text2sql-framework](https://github.com/cpenniman12/text2sql-framework). Plugs into Claude Desktop, Cursor, Goose, or any other MCP-compatible assistant and lets it ask a SQL database questions in natural language.

The agent explores the schema, writes SQL, executes it against the real DB, and self-corrects on errors — no RAG layer, no schema descriptions, no pre-computed embeddings.

## Install

Out of the box, `text2sql-mcp` supports **SQLite + Anthropic**:

```bash
pip install text2sql-mcp
# or
uvx text2sql-mcp
```

For other databases or LLM providers, install with the matching extra so the right driver gets installed:

| You want… | Install command |
| --- | --- |
| SQLite (default) | `uvx text2sql-mcp` |
| Postgres | `uvx 'text2sql-mcp[postgres]'` |
| MySQL | `uvx 'text2sql-mcp[mysql]'` |
| Snowflake | `uvx 'text2sql-mcp[snowflake]'` |
| BigQuery | `uvx 'text2sql-mcp[bigquery]'` |
| OpenAI models | add `openai`, e.g. `uvx 'text2sql-mcp[postgres,openai]'` |

## Configure

Set environment variables in your MCP client config:

| Variable | Required | Description |
| --- | --- | --- |
| `TEXT2SQL_DATABASE_URL` | yes | SQLAlchemy URL, e.g. `sqlite:///mydb.db`, `postgresql://user:pass@host/db` |
| `ANTHROPIC_API_KEY` *or* `OPENAI_API_KEY` | yes | LLM provider key |
| `TEXT2SQL_MODEL` | no | LangChain model id (default: `anthropic:claude-sonnet-4-6`) |
| `TEXT2SQL_INSTRUCTIONS` | no | Business rules / hints, e.g. "Revenue = net of refunds." |
| `TEXT2SQL_EXAMPLES` | no | Path to a scenarios.md file for the agent's `lookup_example` tool |

### Claude Desktop / Cursor / generic MCP

```json
{
  "mcpServers": {
    "text2sql": {
      "command": "uvx",
      "args": ["text2sql-mcp"],
      "env": {
        "TEXT2SQL_DATABASE_URL": "sqlite:///mydb.db",
        "ANTHROPIC_API_KEY": "sk-ant-..."
      }
    }
  }
}
```

### Goose CLI

```bash
goose configure
# Add Extension → Command-line Extension
# Name: text2sql
# Command: uvx text2sql-mcp
# Env: TEXT2SQL_DATABASE_URL, ANTHROPIC_API_KEY
```

## Tools

- **`query(question, max_rows=100)`** — ask the database a natural-language question. Returns `{sql, data, error, row_count, tool_calls_made}`.

## How it works

Under the hood this is a thin wrapper around [text2sql-framework](https://github.com/cpenniman12/text2sql-framework), which uses LangChain Deep Agents to do iterative tool-calling against a single `execute_sql` tool. See the framework README for benchmarks (19/20 on Spider zero-shot across 80 tables) and architecture details.

## License

MIT

TDQS

A4.7/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of confusion between overlapping functions. The tool's purpose is clearly defined for natural-language database queries, making selection trivial.

Naming Consistency5/5

The single tool named 'query' is simple, intuitive, and uses a clear verb form. While there is no pattern to compare, the naming is unambiguous and follows common conventions for a query action.

Tool Count3/5

The server has just one tool, which feels thin for a database interaction service. However, the tool is comprehensive and handles schema exploration, SQL generation, execution, and self-correction internally, so it may be sufficient for its narrow scope.

Completeness5/5

The tool covers the full natural-language query lifecycle: it interprets the question, writes SQL, executes it, and returns results with error handling. As a read-only query tool, it fully addresses the stated purpose without obvious gaps.

Maintenance

ActivitySlowing
ResponsivenessNo issues