Install
$ agentstack add mcp-marekrost-mcp-server-spreadsheet ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
About
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
fileandsheetexplicitly; 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).
Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: marekrost
- Source: marekrost/mcp-server-spreadsheet
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.