Pandas MCP Server
@marlonluo2018
About Pandas MCP Server
No overview available yet
Basic information
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"pandas-mcp-server": {
"command": "python",
"args": [
"cli.py"
]
}
}
}Tools
No tools detected
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
What is Pandas MCP Server?
A Model Context Protocol (MCP) server that enables LLMs to execute pandas code through a standardized workflow for data analysis and visualization. It provides secure, sandboxed code execution, intelligent data analysis, and interactive chart generation for AI assistants like Claude Desktop.
How to use Pandas MCP Server?
Clone the repository, install dependencies (pip install -r requirements.txt), optionally configure environment variables via .env, and then add a JSON entry to your Claude Desktop configuration (using uvx or python). Verify installation by running python cli.py or python server.py. The server exposes four MCP tools: read_metadata_tool, interpret_column_data, run_pandas_code_tool, and generate_chartjs_tool.
Key features of Pandas MCP Server
- Sandboxed execution environment for security
- Automatic file metadata extraction and analysis
- Interactive Chart.js visualization generation
- Intelligent memory optimization for large files
- Easy integration with Claude Desktop
- Command-line interface for testing and development
Use cases of Pandas MCP Server
- Let an LLM explore and analyze CSV or Excel files
- Generate interactive bar, line, or pie charts from data
- Perform secure, guided data cleaning and transformation
- Automate multi-step data analysis workflows with AI
- Interpret categorical columns to improve filtering and aggregation
FAQ from Pandas MCP Server
What are the prerequisites to run Pandas MCP Server?
Python 3.10 or higher, pip package manager, and Git are required. Dependencies include pandas>=2.0.0, fastmcp>=1.0.0, chardet>=5.0.0, and psutil.
What file types does Pandas MCP Server support?
It supports CSV (.csv) and Excel (.xlsx, .xls) files. Excel files can optionally specify a sheet name or index.
What tools does the server expose to LLMs?
Four tools: read_metadata_tool (file analysis), interpret_column_data (column value interpretation), run_pandas_code_tool (code execution), and generate_chartjs_tool (chart generation).
How do I configure Pandas MCP Server with Claude Desktop?
Add a JSON entry with type "stdio" and either "uvx" (recommended) or "python" as the command, pointing to the server directory or server.py. The configuration file is located in %APPDATA%\Claude\claude_desktop_config.json (Windows), ~/Library/Application Support/Claude/claude_desktop_config.json (macOS), or ~/.config/Claude/claude_desktop_config.json (Linux).
Is code execution secure in Pandas MCP Server?
Yes, code runs in a sandboxed environment that prevents malicious operations and protects system security.
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