CSV Server

A Python MCP (Model Context Protocol) server that enables AI assistants to answer natural language questions about company processes and operational data stored in CSV files. Built with FastMCP and Polars for efficient CSV processing with server-side filter expressions.

Technologies

Available Tools

Quick Start

Without Docker

1. Install dependencies:

   pip install mcp polars
   

2. Place your CSV files in the ./data/ directory (or set CSV_DIR to a custom path).

3. Run the server:

   python server.py
   

   The server starts in stdio mode by default, which is what AI clients like Claude Desktop and Cursor expect.

With Docker

1. Place your CSV files in the ./data/ directory.

2. Build and start the container:

   docker compose up -d
   

   The server runs in HTTP mode on http://localhost:8000/mcp.

3. Verify connectivity:

   curl -X POST http://localhost:8000/mcp \
     -H "Content-Type: application/json" \
     -H "Accept: application/json, text/event-stream" \
     -d '{"jsonrpc":"2.0","method":"initialize","params":{"protocolVersion":"2024-11-05","capabilities":{},"clientInfo":{"name":"test","version":"0.1"}},"id":1}'
   

Configuration

Environment Variables

AI Client Integration

OpenCode

Add to your opencode.json:

Local (stdio):

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "csv-mcp": {
      "type": "local",
      "command": ["python", "server.py"],
      "environment": {
        "CSV_DIR": "./data"
      },
      "enabled": true
    }
  }
}

Docker (HTTP):

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "csv-mcp": {
      "type": "remote",
      "url": "http://localhost:8000/mcp",
      "enabled": true
    }
  }
}

Claude Desktop / Cursor

For stdio mode:

{
  "mcpServers": {
    "csv-mcp": {
      "command": "python",
      "args": ["/path/to/server.py"],
      "env": {
        "CSV_DIR": "/path/to/data"
      }
    }
  }
}

For Docker (HTTP):

{
  "mcpServers": {
    "csv-mcp": {
      "url": "http://localhost:8000/mcp"
    }
  }
}

Usage Examples

Once connected, ask your AI assistant questions like:

• "List all available CSV files"
• "Show the schema of processes.csv"
• "Find all rows where status equals 'active' in processes.csv"

The ask_csv_question tool accepts Polars filter expressions:

Testing

# Run all tests
python -m pytest tests/ -v

# Run with coverage
COVERAGE_FILE=/tmp/.coverage python -m pytest tests/ --cov=server --cov-report=term-missing

Security

• Path traversal protection: All file paths are resolved and validated to stay within CSV_DIR
• Expression sanitization: Filter expressions are checked against dangerous patterns (import, exec, eval, etc.) before evaluation