Spreadsheet MCP

MCP server for spreadsheet analysis and editing. Slim, token-efficient tool surface designed for LLM agents.

Why?

Dumping a 50,000-row spreadsheet into an LLM context is expensive and usually unnecessary. Most spreadsheet tasks need surgical access: find a region, profile its structure, read a filtered slice. This server exposes tools that let agents discover → profile → extract without burning tokens on cells they don't need.

• Full support: .xlsx (via umya-spreadsheet)
• Discovery only: .xls, .xlsb (enumerated, not parsed)

Architecture

• LRU cache keeps recently-accessed workbooks in memory (configurable capacity)
• Lazy sheet metrics computed once per sheet, reused across tools
• Region detection runs once and caches bounds for sheet_overview, find_value, read_table, table_profile

Tool Surface

Tool	Purpose
list_workbooks, list_sheets	Discover targets and get sheet summaries
workbook_summary	Region counts/kinds, named ranges, suggested entry points
sheet_overview	Detected regions (bounds/id/kind/confidence), narrative, key ranges
find_value	Value/label-mode lookup with region/table scoping, neighbors, row context
read_table	Structured read (range/region/table/named range), headers, filters, sampling
table_profile	Lightweight column profiling with samples and inferred types
range_values	Minimal range fetch for spot checks
sheet_page	Fallback pagination; supports compact/values_only
formula_trace	Precedents/dependents with paging

Write & Recalc Support

Write tools allow "what-if" analysis: fork a workbook, edit cells, recalculate formulas via LibreOffice, and diff the results.

Enabling Write Tools

Always use the :full Docker image for write/recalc features:

docker run -v /path/to/workbooks:/data -p 8079:8079 ghcr.io/psu3d0/spreadsheet-mcp:full

The Docker image includes LibreOffice with pre-configured macros required for reliable recalculation. Running outside Docker requires manual LibreOffice setup (macro trust, headless config) and is not recommended.

Write Tools

Tool	Purpose
create_fork	Create a temporary editable copy for "what-if" analysis
edit_batch	Apply values or formulas to cells in a fork
recalculate	Trigger LibreOffice to update formula results
get_changeset	Diff the fork against the original (cells, tables, named ranges)
get_edits	List all edits applied to a fork
list_forks	List all active forks
save_fork	Save fork to a new path (or overwrite original with --allow-overwrite)
discard_fork	Delete the temporary fork

See docs/RECALC.md for architecture details.

Example

Request: Profile a detected region

{
  "tool": "table_profile",
  "arguments": {
    "workbook_id": "budget-2024-a1b2c3",
    "sheet_name": "Q1 Actuals",
    "region_id": 1,
    "sample_size": 10,
    "sample_mode": "distributed"
  }
}

Response:

{
  "sheet_name": "Q1 Actuals",
  "headers": ["Date", "Category", "Amount", "Notes"],
  "column_types": [
    {"name": "Date", "inferred_type": "date", "nulls": 0, "distinct": 87},
    {"name": "Category", "inferred_type": "text", "nulls": 2, "distinct": 12, "top_values": ["Payroll", "Marketing", "Infrastructure"]},
    {"name": "Amount", "inferred_type": "number", "nulls": 0, "min": 150.0, "max": 84500.0, "mean": 12847.32},
    {"name": "Notes", "inferred_type": "text", "nulls": 45, "distinct": 38}
  ],
  "row_count": 1247,
  "samples": [...]
}

The agent now knows column types, cardinality, and value distributions—without reading 1,247 rows.

Recommended Agent Workflow

1. list_workbooks → list_sheets → workbook_summary for orientation
2. sheet_overview to get detected_regions (ids/bounds/kind/confidence)
3. table_profile → read_table with region_id, small limit, and sample_mode (distributed preferred)
4. Use find_value (label mode) or range_values for targeted pulls
5. Reserve sheet_page for unknown layouts or calculator inspection; prefer compact/values_only
6. Keep payloads small; page/filter rather than full-sheet reads

Region Detection

Spreadsheets often contain multiple logical tables, parameter blocks, and output areas on a single sheet. The server detects these automatically:

1. Gutter detection — Scans for empty rows/columns that separate content blocks
2. Recursive splitting — Subdivides large areas along detected gutters
3. Border trimming — Removes sparse edges to tighten bounds
4. Header detection — Identifies header rows (including multi-row merged headers)
5. Classification — Labels each region: data, parameters, outputs, calculator, metadata
6. Confidence scoring — Higher scores for well-structured regions with clear headers

Regions are cached per sheet. Tools like read_table accept a region_id to scope reads without manually specifying ranges.

Quick Start

Docker (Recommended)

Two image variants are published:

Image	Size	Write/Recalc
ghcr.io/psu3d0/spreadsheet-mcp:latest	~15MB	No
ghcr.io/psu3d0/spreadsheet-mcp:full	~800MB	Yes (includes LibreOffice)

# Read-only (slim image)
docker run -v /path/to/workbooks:/data -p 8079:8079 ghcr.io/psu3d0/spreadsheet-mcp:latest

# With write/recalc support (full image)
docker run -v /path/to/workbooks:/data -p 8079:8079 ghcr.io/psu3d0/spreadsheet-mcp:full

Cargo Install

# Read-only
cargo install spreadsheet-mcp
spreadsheet-mcp --workspace-root /path/to/workbooks

Note: For write/recalc features, use the :full Docker image instead of cargo install. The Docker image includes LibreOffice with required macro configuration.

Build from Source

cargo run --release -- --workspace-root /path/to/workbooks

Default transport: HTTP streaming at 127.0.0.1:8079. Endpoint: POST /mcp.

Use --transport stdio for CLI pipelines.

MCP Client Configuration

Claude Code / Claude Desktop

Add to ~/.claude.json or project .mcp.json:

Read-only (slim image):

{
  "mcpServers": {
    "spreadsheet": {
      "command": "docker",
      "args": ["run", "-i", "--rm", "-v", "/path/to/workbooks:/data", "ghcr.io/psu3d0/spreadsheet-mcp:latest", "--transport", "stdio"]
    }
  }
}

With write/recalc (full image):

{
  "mcpServers": {
    "spreadsheet": {
      "command": "docker",
      "args": ["run", "-i", "--rm", "-v", "/path/to/workbooks:/data", "ghcr.io/psu3d0/spreadsheet-mcp:full", "--transport", "stdio"]
    }
  }
}

Binary (no Docker):

{
  "mcpServers": {
    "spreadsheet": {
      "command": "spreadsheet-mcp",
      "args": ["--workspace-root", "/path/to/workbooks", "--transport", "stdio"]
    }
  }
}

Cursor / VS Code

Read-only (slim image):

{
  "mcp.servers": {
    "spreadsheet": {
      "command": "docker",
      "args": ["run", "-i", "--rm", "-v", "${workspaceFolder}:/data", "ghcr.io/psu3d0/spreadsheet-mcp:latest", "--transport", "stdio"]
    }
  }
}

With write/recalc (full image):

{
  "mcp.servers": {
    "spreadsheet": {
      "command": "docker",
      "args": ["run", "-i", "--rm", "-v", "${workspaceFolder}:/data", "ghcr.io/psu3d0/spreadsheet-mcp:full", "--transport", "stdio"]
    }
  }
}

Binary (no Docker):

{
  "mcp.servers": {
    "spreadsheet": {
      "command": "spreadsheet-mcp",
      "args": ["--workspace-root", "${workspaceFolder}", "--transport", "stdio"]
    }
  }
}

HTTP Mode

docker run -v /path/to/workbooks:/data -p 8079:8079 ghcr.io/psu3d0/spreadsheet-mcp:latest

Connect via POST http://localhost:8079/mcp.

Local Development

To test local changes without rebuilding Docker:

cargo build --release

Then point your MCP client to the binary:

{
  "mcpServers": {
    "spreadsheet": {
      "command": "/path/to/spreadsheet-mcp/target/release/spreadsheet-mcp",
      "args": ["--workspace-root", "/path/to/workbooks", "--transport", "stdio"]
    }
  }
}

Configuration

Flag	Env	Description
--workspace-root <DIR>	SPREADSHEET_MCP_WORKSPACE	Workspace root to scan (default: cwd)
--cache-capacity <N>	SPREADSHEET_MCP_CACHE_CAPACITY	Workbook cache size (default: 5)
--extensions <list>	SPREADSHEET_MCP_EXTENSIONS	Allowed extensions (default: xlsx,xls,xlsb)
--workbook <FILE>	SPREADSHEET_MCP_WORKBOOK	Single-workbook mode
--enabled-tools <list>	SPREADSHEET_MCP_ENABLED_TOOLS	Whitelist exposed tools
--transport <http|stdio>	SPREADSHEET_MCP_TRANSPORT	Transport selection (default: http)
--http-bind <ADDR>	SPREADSHEET_MCP_HTTP_BIND	Bind address (default: 127.0.0.1:8079)
--recalc-enabled	SPREADSHEET_MCP_RECALC_ENABLED	Enable write/recalc tools (default: false)
--max-concurrent-recalcs <N>	SPREADSHEET_MCP_MAX_CONCURRENT_RECALCS	Parallel recalc limit (default: 2)
--allow-overwrite	SPREADSHEET_MCP_ALLOW_OVERWRITE	Allow save_fork to overwrite original files (default: false)

Performance

• LRU workbook cache — Recently opened workbooks stay in memory; oldest evicted when capacity exceeded
• Lazy metrics — Sheet metrics computed on first access, cached for subsequent calls
• Region caching — Detection runs once per sheet; region_id lookups are O(1)
• Sampling modes — distributed sampling reads evenly across rows without loading everything
• Compact formats — values_only and compact output modes reduce response size

Testing

cargo test

Covers: region detection, region-scoped tools, read_table edge cases (merged headers, filters, large sheets), workbook summary.

Local MCP Testing

To test local changes with an MCP client (Claude Code, Cursor, etc.), use the helper script that rebuilds the Docker image on each invocation:

{
  "mcpServers": {
    "spreadsheet": {
      "command": "./scripts/local-docker-mcp.sh"
    }
  }
}

Set WORKSPACE_ROOT to override the default test directory:

WORKSPACE_ROOT=/path/to/workbooks ./scripts/local-docker-mcp.sh

This ensures you're always testing against your latest code changes without manual image rebuilds.

Behavior & Limits

• Read-only by default; write/recalc features require --recalc-enabled or the :full image
• XLSX supported for write; .xls/.xlsb are read-only
• Bounded in-memory cache honors cache_capacity
• Prefer region-scoped reads and sampling for token/latency efficiency