mcp-server-spreadsheet

mcp-server-spreadsheet

mcp-name: io.github.marekrost/mcp-server-spreadsheet

Data-first MCP server for reading and writing spreadsheet files (.xlsx, .csv, .ods).

Key features

• Multi-format — works with Excel (.xlsx), CSV (.csv), and OpenDocument (.ods) files through a unified tool interface.
• Dual mode — cell-level workbook operations and a DuckDB-powered SQL query engine, interleaved freely on the same file.
• Workbook essentials — worksheets, rows, columns, cells, search.
• Data-only — preserves existing formatting but only reads and writes values.
• Stateless — every call specifies file and sheet explicitly; no handles or sessions.
• Atomic saves — writes go to a temp file, then os.replace() into the target path.
• Type coercion on write — numeric strings become numbers, everything else is text.
• SQL across sheets — JOINs, GROUP BY, aggregates, subqueries via in-memory DuckDB; mutations write back to the file.
• CSV as single-sheet workbook — CSV files are treated as a workbook with one sheet named default.

Requirements

• Python 3.10+

Installation

From PyPI (recommended)

No local checkout needed — just configure your MCP client (see below).

From source (for development)

git clone https://github.com/marekrost/mcp-server-spreadsheet.git
cd mcp-server-spreadsheet
uv sync

Usage

Claude Desktop

Add to your claude_desktop_config.json:

Using PyPI (recommended):

{
  "mcpServers": {
    "mcp-server-spreadsheet": {
      "command": "uvx",
      "args": ["mcp-server-spreadsheet"]
    }
  }
}

Using local source:

{
  "mcpServers": {
    "mcp-server-spreadsheet": {
      "command": "uv",
      "args": ["run", "--directory", "/path/to/mcp-server-spreadsheet", "main.py"]
    }
  }
}

Claude Code

Add to your .mcp.json:

Using PyPI (recommended):

{
  "mcpServers": {
    "mcp-server-spreadsheet": {
      "command": "uvx",
      "args": ["mcp-server-spreadsheet"]
    }
  }
}

Using local source:

{
  "mcpServers": {
    "mcp-server-spreadsheet": {
      "command": "uv",
      "args": ["run", "--directory", "/path/to/mcp-server-spreadsheet", "main.py"]
    }
  }
}

Standalone (stdio transport)

# PyPI
uvx mcp-server-spreadsheet

# Local source
uv run main.py

Restricting file access to a directory (optional)

Set MCP_SPREADSHEET_ROOT to confine all path arguments to a single directory tree. Paths outside it are rejected with a clear error returned to the agent.

{
  "mcpServers": {
    "mcp-server-spreadsheet": {
      "command": "uvx",
      "args": ["mcp-server-spreadsheet"],
      "env": { "MCP_SPREADSHEET_ROOT": "/home/me/spreadsheets" }
    }
  }
}

Unset (the default), any path the server process can access is allowed.

Format notes

Format	Sheets	Formulas	Types
.xlsx	Multiple	Preserved as strings	Native (int, float, date, bool)
.ods	Multiple	Not preserved	Native (int, float, date, bool)
.csv	Single (default)	N/A	Inferred on load (int, float, text)

Sheet management tools (add_sheet, delete_sheet, copy_sheet) raise an error for CSV files.

Tools

Workbook Operations

Tool	Description
list_workbooks	List all spreadsheet files in a directory (non-recursive)
create_workbook_file	Create a new empty spreadsheet file (format by extension)
copy_workbook	Copy an existing file to a new path

Sheet Operations

Tool	Description
list_sheets	List all sheet names in a workbook
add_sheet	Add a new sheet (optional name and position)
rename_sheet	Rename an existing sheet
delete_sheet	Delete a sheet by name
copy_sheet	Duplicate a sheet within a workbook (optional new name and position)

Reading Data

Tool	Description
read_sheet	Read entire sheet as rows (optional row/column bounds)
read_cell	Read a single cell value, e.g. B3
read_range	Read a rectangular range, e.g. A1:D10
get_sheet_dimensions	Get row and column count of the used range

Writing Data

Tool	Description
write_cell	Write a value to a single cell
write_range	Write a 2D array starting at a given cell
append_rows	Append rows after the last used row
insert_rows	Insert blank or pre-filled rows at a position (shifts rows down)
delete_rows	Delete rows by index (shifts rows up)
clear_range	Clear values in a range without removing rows/columns
copy_range	Copy a block of cells to another location (optionally to a different sheet)

Column Operations

Tool	Description
insert_columns	Insert blank columns at a position
delete_columns	Delete columns by index

Search

Tool	Description
search_sheet	Search for a value or regex pattern, returns matching cell references

Table Mode (SQL)

Tool	Description
describe_table	Inspect column names, inferred types, row count, and sample values
sql_query	Execute a read-only SQL SELECT (supports JOINs across sheets, GROUP BY, aggregates, subqueries)
sql_execute	Execute INSERT INTO, UPDATE, or DELETE FROM — writes changes back to the file

SQL examples:

-- Filter and sort
SELECT name, revenue FROM Sales WHERE status = 'Active' ORDER BY revenue DESC LIMIT 20

-- Cross-sheet JOIN
SELECT o.order_id, c.name FROM Orders o JOIN Customers c ON o.customer_id = c.id

-- Aggregate
SELECT department, COUNT(*) AS n, AVG(salary) AS avg FROM Employees GROUP BY department

-- Mutate
UPDATE Sales SET status = 'Closed' WHERE quarter = 'Q1' AND revenue < 1000
DELETE FROM Logs WHERE date < '2024-01-01'

Sheet names with spaces must be quoted: SELECT * FROM "Q1 Sales".

Sheets whose table doesn't start at row 1

All three SQL tools accept header_row and data_start_row. Each can be an int (applied to every sheet) or a {sheet_name: row} mapping (sheets not listed fall back to the default). Use header_row when column titles live below row 1, and data_start_row when extra rows (e.g. a units row) sit between the header and the data.

# Header on row 3, data follows immediately
sql_query(file, 'SELECT * FROM "People"', header_row=3)

# Mixed workbook: People headers at row 3, Orders header at row 1 with a
# units row at row 2.
sql_query(
    file,
    'SELECT * FROM "Orders" o JOIN "People" p ON o.name = p.name',
    header_row={"People": 3, "Orders": 1},
    data_start_row={"Orders": 3},
)

sql_execute preserves rows above header_row when writing changes back.

Running tests

uv sync --group dev
uv run pytest

Every tool is exercised against .xlsx, .csv, and .ods fixtures generated into a temp directory.

Common Parameters

Every sheet-level tool accepts:

Parameter	Required	Description
file	yes	Path to the spreadsheet file (.xlsx, .csv, or .ods)
sheet	no	Sheet name. Defaults to the first sheet in the workbook

All row/column indices are 1-based. Cell references use A1 notation (A1, $B$2).