io.github.marekrost/mcp-server-spreadsheet
MCP server for spreadsheet files (.xlsx, .csv, .ods) - cell-level ops + DuckDB SQL engine.
Open source Open in the app JSON README (API)
About
MCP server for spreadsheet files (.xlsx, .csv, .ods) - cell-level ops + DuckDB SQL engine.
Details
- Kind
- MCP servers
- Topic
- Files & documents
- Publisher
- marekrost
- Origin
- official
- Category
- ferramentas
- Transport
- local
- Version
- 0.3.3
- Stars
- 2
- Forks
- 1
- Last push
- 2026-08-11T11:47:39Z
- Repository state
- ativo
- Language
- Python
- License
- MIT
- Added
- 2026-08-29 04:00:27
- Updated
- 2026-08-29 04:00:27
- Origin id
io.github.marekrost/mcp-server-spreadsheet
README
# 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)
```bash
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):**
```json
{
"mcpServers": {
"mcp-server-spreadsheet": {
"command": "uvx",
"args": ["mcp-server-spreadsheet"]
}
}
}
```
**Using local source:**
```json
{
"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):**
```json
{
"mcpServers": {
"mcp-server-spreadsheet": {
"command": "uvx",
"args": ["mcp-server-spreadsheet"]
}
}
}
```
**Using local source:**
```json
{
"mcpServers": {
"mcp-server-spreadsheet": {
"command": "uv",
"args": ["run", "--directory", "/path/to/mcp-server-spreadsheet", "main.py"]
}
}
}
```
### Standalone (stdio transport)
```bash
# 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.
```json
{
"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:
```sql
-- 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.
```python
# 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
```bash
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`).