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📊 Server name: Excel Explorer
📦 Transport: Streamable-HTTP / Direct
🔗 Server URL: http://127.0.0.1:8000/mcp
📚 Docs: https://gofastmcp.com
🚀 Deploy: https://fastmcp.cloud
⚡ FastMCP version: 2.10.6
🔧 MCP version: 1.12.3
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📊 Excel MCP Server
What is this project?
Excel MCP Server is a Model Context Protocol (MCP) server that allows Large Language Models (like Claude) to read, explore, and analyze Excel files. It provides tools for:
- 📂 File Operations: Load Excel files, list sheets, get metadata
- 🔍 Data Discovery: Analyze schemas, sample data, get column statistics
- 📊 Analysis: Comprehensive dataset summaries and data quality reports
Built with FastMCP and pandas, it transforms your Excel files into interactive datasets that AI can understand and query.
Install Dependencies
# Set up environment (optional)
source activate-pipx.sh
# Install dependencies
uv sync
Requirements:
- Python >=3.13
- fastmcp >=2.10.6
- pandas >=2.3.1
- openpyxl >=3.1.5
- xlrd >=2.0.2
- pytest >=8.4.1
Start the MCP Server
python main.py
or
fastmcp run main.py:mcp --transport http --host 127.0.0.1 --port 8000 --path /mcp
The server will start and listen for MCP connections. You'll see output confirming the server is running.
Testing
# Run all tests
python -m pytest tests/ -v
# Run specific test files
python -m pytest tests/test_file_operations.py -v
python -m pytest tests/test_data_discovery.py -v
# With coverage
python -m pytest tests/ --cov=src --cov-report=html
Integrate with Claude
1. Claude Desktop Integration
Add to your Claude Desktop config file (claude_desktop_config.json):
{
"mcpServers": {
"excel-explorer": {
"command": "python",
"args": ["/path/to/excel-mcp/main.py"],
"env": {}
}
}
}
or
{
"excelExplorer": {
"command": "npx",
"args": [
"-y",
"mcp-remote",
"http://127.0.0.1:8000/mcp"
],
"env": {
"MCP_TRANSPORT_STRATEGY": "http-only"
}
}
}
2. Available Tools
Once connected, Claude can use these tools:
File Operations:
load_excel(file_path, sheet_name)- Load Excel filelist_sheets(file_path)- List all sheetsget_file_info(file_path)- File metadataclear_cache()- Clear memory
Data Discovery:
get_schema(file_path, sheet_name)- Column types and statsget_sample_data(file_path, rows=5, sample_type="head")- Sample dataget_column_info(file_path, column_name)- Column analysisget_dimensions(file_path)- Dataset size and memorydescribe_dataset(file_path, include_all=False)- Statistical summary
3. Example Usage with Claude
You: "Load the file data/dataset.xlsx and tell me about its structure"
Claude will use:
1. load_excel("data/dataset.xlsx")
2. get_schema("data/dataset.xlsx")
3. get_dimensions("data/dataset.xlsx")
4. describe_dataset("data/dataset.xlsx")
Then provide insights about your data!
Ready to explore your Excel data with AI! 🚀📊