excel-mcp

sbroenne/mcp-server-excel · updated Apr 8, 2026

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$npx skills add https://github.com/sbroenne/mcp-server-excel --skill excel-mcp
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summary

Automate Excel workbooks on Windows with 226 COM-based operations covering data, formulas, tables, Power Query, and DAX.

  • Supports full Excel object model: ranges, tables, worksheets, PivotTables, charts, slicers, conditional formatting, and VBA macro execution
  • Includes Power Query (M code evaluation and creation) and Data Model (DAX measures) for advanced analytics workflows
  • Provides calculation mode control for batch write performance optimization when handling large data volumes
skill.md

Excel MCP Server Skill

Provides 227 Excel operations via Model Context Protocol. The MCP Server forwards all requests to the shared ExcelMCP Service, enabling session sharing with CLI. Tools are auto-discovered - this documents quirks, workflows, and gotchas.

Workflow Checklist

Step Tool Action When
1. Open file file open or create Always first
2. Create sheets worksheet create, rename If needed
3. Write data range set-values Always (2D arrays)
4. Format range set-number-format After writing
5. Structure table create Convert data to tables
6. Save & close file close with save: true Always last

Preconditions

  • Windows host with Microsoft Excel installed (2016+)
  • Use full Windows paths: C:\Users\Name\Documents\Report.xlsx
  • Excel files must not be open in another Excel instance

Calculation Mode Workflow (Batch Performance)

Use calculation_mode for bulk write performance optimization. When writing many values or formulas, disable auto-recalc to avoid recalculating after every cell:

1. calculation_mode(action: 'set-mode', mode: 'manual')  → Disable auto-recalc
2. Perform all writes (range set-values, set-formulas)
3. calculation_mode(action: 'calculate', scope: 'workbook')  → Recalculate once
4. calculation_mode(action: 'set-mode', mode: 'automatic')  → Restore default

Note: You do NOT need manual mode to read formulas - range get-formulas returns formula text regardless of calculation mode.

CRITICAL: Execution Rules (MUST FOLLOW)

Rule 1: NEVER Ask Clarifying Questions

STOP. If you're about to ask "Which file?", "What table?", "Where should I put this?" - DON'T.

Bad (Asking) Good (Discovering)
"Which Excel file should I use?" file(list) → use the open session
"What's the table name?" table(list) → discover tables
"Which sheet has the data?" worksheet(list) → check all sheets
"Should I create a PivotTable?" YES - create it on a new sheet

You have tools to answer your own questions. USE THEM.

Rule 2: Always End With a Text Summary

NEVER end your turn with only a tool call. After completing all operations, always provide a brief text message confirming what was done. Silent tool-call-only responses are incomplete.

Rule 3: Format Data Professionally

Always apply number formats after setting values:

Data Type Format Code Result
USD $#,##0.00 $1,234.56
EUR €#,##0.00 €1,234.56
Percent 0.00% 15.00%
Date (ISO) yyyy-mm-dd 2025-01-22

Workflow:

1. range set-values (data is now in cells)
2. range set-number-format (apply format)

Rule 4: Use Excel Tables (Not Plain Ranges)

Always convert tabular data to Excel Tables:

1. range set-values (write data including headers)
2. table create tableName="SalesData" rangeAddress="A1:D100"

Why: Structured references, auto-expand, required for Data Model/DAX.

Rule 5: Session Lifecycle

1. file(action: 'open', path: '...')  → sessionId
2. All operations use sessionId
3. file(action: 'close', save: true)  → saves and closes

Unclosed sessions leave Excel processes running, locking files.

Rule 6: Data Model Prerequisites

DAX operations require tables in the Data Model:

Step 1: Create table → Table exists
Step 2: table(action: 'add-to-datamodel') → Table in Data Model
Step 3: datamodel(action: 'create-measure') → NOW this works

Rule 7: Power Query Development Lifecycle

BEST PRACTICE: Test-First Workflow

1. powerquery(action: 'evaluate', mCode: '...') → Test WITHOUT persisting
2. powerquery(action: 'create', ...) → Store validated query
3. powerquery(action: 'refresh', ...) → Load data

Why evaluate first:

  • Catches syntax errors and missing sources BEFORE creating permanent queries
  • Better error messages than COM exceptions from create/update
  • See actual data preview (columns + sample rows)
  • No cleanup needed - like a REPL for M code
  • Skip only for trivial literal tables

Common mistake: Creating/updating without evaluate → pollutes workbook with broken queries

Rule 8: Targeted Updates Over Delete-Rebuild

  • Prefer: set-values on specific range (e.g., A5:C5 for row 5)
  • Avoid: Deleting and recreating entire structures

Why: Preserves formatting, formulas, and references.

Rule 9: Follow suggestedNextActions

Error responses include actionable hints:

{
  "success": false,
  "errorMessage": "Table 'Sales' not found in Data Model",
  "suggestedNextActions": ["table(action: 'add-to-data-model', tableName: 'Sales')"]
}

Rule 10: Use Calculation Mode for Bulk Write Performance

When writing many values/formulas (10+ cells), use calculation_mode to avoid recalculating after every write:

1. calculation_mode(action: 'set-mode', mode: 'manual')  → Disable auto-recalc
2. Perform data writes (range set-values, set-formulas)
3. calculation_mode(action: 'calculate', scope: 'workbook')  → Recalculate once at end
4. calculation_mode(action: 'set-mode', mode: 'automatic')  → Restore default

When NOT needed: Reading formulas, small edits (1-10 cells), or when you need immediate calculation results.

Tool Selection Quick Reference

Task Tool Key Action
Create/open/save workbooks file open, create, close
Write/read cell data range set-values, get-values
Format cells range set-number-format
Create tables from data table create
Add table to Power Pivot table add-to-data-model
Create DAX formulas datamodel create-measure
Create PivotTables pivottable create, create-from-datamodel
Filter with slicers slicer set-slicer-selection
Create charts chart create-from-range
Control calculation mode calculation_mode get-mode, set-mode, calculate
Visual verification screenshot capture, capture-sheet

Reference Documentation

See references/ for detailed guidance:

how to use excel-mcp

How to use excel-mcp on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add excel-mcp
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/sbroenne/mcp-server-excel --skill excel-mcp

The skills CLI fetches excel-mcp from GitHub repository sbroenne/mcp-server-excel and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/excel-mcp

Reload or restart Cursor to activate excel-mcp. Access the skill through slash commands (e.g., /excel-mcp) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.661 reviews
  • Aarav Patel· Dec 28, 2024

    We added excel-mcp from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Chaitanya Patil· Dec 24, 2024

    excel-mcp has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Chinedu Agarwal· Dec 24, 2024

    excel-mcp reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Aarav Kapoor· Dec 24, 2024

    I recommend excel-mcp for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Soo Sethi· Dec 20, 2024

    Solid pick for teams standardizing on skills: excel-mcp is focused, and the summary matches what you get after install.

  • Henry Mehta· Dec 16, 2024

    excel-mcp is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Aanya Agarwal· Nov 19, 2024

    Useful defaults in excel-mcp — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Piyush G· Nov 15, 2024

    Solid pick for teams standardizing on skills: excel-mcp is focused, and the summary matches what you get after install.

  • Soo Taylor· Nov 11, 2024

    excel-mcp has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Aanya Bansal· Nov 7, 2024

    Keeps context tight: excel-mcp is the kind of skill you can hand to a new teammate without a long onboarding doc.

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