excel-mcp

An MCP (Model Context Protocol) server for reading Excel workbooks (.xlsx). Built with FastMCP and openpyxl.

Features

• List all sheets in a workbook

• List all named tables across sheets

• List all pivot tables with source range info

• Read raw cell data from any sheet or optional cell range

• Read structured data (headers + rows) from named Excel tables

• Export any sheet to CSV, plain-text (delimited), or Markdown — save to file or return inline

Related MCP server: Excel MCP Server

Usage with Claude Desktop

No installation required. Add the following to your claude_desktop_config.json:

{
  "mcpServers": {
    "excel-mcp": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/urjeetpatel/excel_mcp_server",
        "excel-mcp"
      ]
    }
  }
}

uvx will pull the package directly from GitHub and run it in an isolated environment — no pip install or virtual environment setup needed.

Running manually

uvx --from git+https://github.com/urjeetpatel/excel_mcp_server excel-mcp

Tools

All tools accept a file_path parameter — the full path to the .xlsx file.

Write tool details

create_blank_file(file_path)

Creates a new blank Excel file at the specified path.

add_sheet(file_path, sheet_name)

Adds a new sheet to the Excel file. Fails if the sheet already exists.

add_data_to_sheet(file_path, sheet_name, data, start_cell="A1")

Adds a 2D array of data to the specified sheet, starting at the given cell (default A1).

add_table_to_sheet(file_path, sheet_name, table_name, ref)

Adds a table to the specified sheet, covering the given cell range (e.g. "A1:D10").

set_cell_value(file_path, sheet_name, cell, value)

Sets the value of a single cell (e.g. C5) in the specified sheet.

set_cell_formula(file_path, sheet_name, cell, formula)

Sets a formula (e.g. "=SUM(A1:A10)") in a single cell in the specified sheet.

Tool details

list_sheets(file_path)

["Sheet1", "Sheet2"]

list_tables(file_path)

[{ "name": "SalesTable", "sheet": "Sheet1", "ref": "A1:D20" }]

list_pivot_tables(file_path)

[{
  "name": "PivotTable1",
  "sheet": "Summary",
  "ref": "A1:C10",
  "source_sheet": "RawData",
  "source_ref": "A1:F500"
}]

get_sheet_data(file_path, sheet_name, cell_range?)

{
  "sheet": "Sheet1",
  "range": "A1:D10",
  "rows": [["Name", "Age", "City"], ["Alice", 30, "New York"]]
}

• cell_range is optional. When omitted, the full used range is returned.

• Range strings are case-insensitive (a1:d10 == A1:D10).

get_table_data(file_path, table_name)

{
  "table": "PeopleTable",
  "sheet": "Sheet1",
  "ref": "A1:C4",
  "headers": ["Name", "Age", "City"],
  "rows": [["Alice", 30, "New York"], ["Bob", 25, "Chicago"]]
}

Export tools

All three export tools share a common pattern:

• output_path — path to write the output file, or "return inline" to skip writing and return the content directly in the response.

• cell_range — optional Excel range string (e.g. A1:D10). When omitted, the full used range is exported.

When saving to a file the response contains output_path. When returning inline, output_path is replaced by content.

export_sheet_to_csv(file_path, sheet_name, output_path, delimiter?, cell_range?)

Exports a sheet using Python's csv module (values containing the delimiter or newlines are properly quoted).

delimiter options: "comma" (default), "pipe", "tab".

{ "output_path": "/tmp/data.csv", "sheet": "Sheet1", "range": "A1:C4", "rows_written": 4 }

Inline variant (output_path = "return inline"):

{ "content": "Name,Age,City\r\nAlice,30,New York\r\n...", "sheet": "Sheet1", "range": "A1:C4", "rows_written": 4 }

export_sheet_to_text(file_path, sheet_name, output_path, delimiter?, cell_range?)

Exports a sheet as a plain delimited text file — values are joined with the delimiter with no CSV quoting, making output easy to read or pipe into other tools.

delimiter options: "pipe" (default), "comma", "tab".

{ "output_path": "/tmp/data.txt", "sheet": "Sheet1", "range": "A1:C4", "rows_written": 4 }

Inline variant:

{ "content": "Name|Age|City\nAlice|30|New York\n...", "sheet": "Sheet1", "range": "A1:C4", "rows_written": 4 }

export_sheet_to_markdown(file_path, sheet_name, output_path, cell_range?)

Exports a sheet as a padded Markdown table. The first row is used as the header; a separator line is inserted beneath it. All columns are padded to align.

{ "output_path": "/tmp/data.md", "sheet": "Sheet1", "range": "A1:C4", "rows_written": 4 }

Inline variant:

{ "content": "| Name  | Age | City     |\n| ----- | --- | -------- |\n| Alice | 30  | New York |\n...", "sheet": "Sheet1", "range": "A1:C4", "rows_written": 4 }

Local development

Requires Python >= 3.14 and uv.

git clone https://github.com/urjeetpatel/excel_mcp_server
cd excel_mcp_server
uv sync --group dev

# Run tests
uv run pytest

# Type check
uv run mypy src

Project Structure

src/excel_mcp/
├── __init__.py       # Exposes main() entry point
├── server.py         # FastMCP server and tool registration
├── workbook.py       # Workbook loading helpers
└── tools/
    ├── __init__.py
    ├── read.py       # Read tool implementations
    └── export.py     # Export tool implementations (CSV, text, Markdown)
tests/
├── conftest.py       # pytest fixtures (builds workbooks programmatically)
├── test_read.py      # Tests for read tools
├── test_export.py    # Tests for export tools
└── test_workbook.py  # Tests for workbook helpers

Notes

• Workbooks are opened in data_only=True mode — formula results are read, not formula strings.

• Export tools support "return inline" as output_path to return content directly to the agent without touching the filesystem.

License

GPL-3.0-or-later