FastMCP 2.0 ────────────────────────────────────────────────────────────────────

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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 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.

# 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

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.

# 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

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"
        }
    }
}

Once connected, Claude can use these tools:

File Operations:

• load_excel(file_path, sheet_name) - Load Excel file
• list_sheets(file_path) - List all sheets
• get_file_info(file_path) - File metadata
• clear_cache() - Clear memory

Data Discovery:

• get_schema(file_path, sheet_name) - Column types and stats
• get_sample_data(file_path, rows=5, sample_type="head") - Sample data
• get_column_info(file_path, column_name) - Column analysis
• get_dimensions(file_path) - Dataset size and memory
• describe_dataset(file_path, include_all=False) - Statistical summary

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! 🚀📊