excel-mcp▌
sbroenne/mcp-server-excel · updated Apr 8, 2026
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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
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-valueson specific range (e.g.,A5:C5for 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:
- Core execution rules and LLM guidelines
- Common mistakes to avoid
- Bulk write performance optimization
- Data Model constraints and patterns
- Charts and formatting
- Conditional formatting operations
- Dashboard and report best practices
- Data Model/DAX specifics
- DMV query reference for Data Model analysis
- Power Query M code syntax reference
- PivotTable operations
- Power Query specifics
- Range operations and number formats
- Screenshot and visual verification
- Slicer operations
- Table operations
- Worksheet operations
How to use excel-mcp on Cursor
AI-first code editor with Composer
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
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches excel-mcp from GitHub repository sbroenne/mcp-server-excel and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
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
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.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 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▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★61 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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