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How to Prompt DocuMCP Effectively

This guide shows you how to interact with DocuMCP using effective prompts to get the best results from the system.

Quick Start​

DocuMCP responds to natural language prompts. Here are the most common patterns:

Basic Analysis​

analyze my repository for documentation needs

Get Recommendations​

what static site generator should I use for my project?

Deploy Documentation​

set up GitHub Pages deployment for my docs

Available Tools​

DocuMCP provides several tools you can invoke through natural prompts:

1. Repository Analysis​

Purpose: Analyze your project structure, dependencies, and documentation needs.

Example Prompts:

  • "Analyze my repository structure"
  • "What documentation gaps do I have?"
  • "Examine my project for documentation opportunities"

What it returns: Project analysis with language detection, dependency mapping, and complexity assessment.

2. SSG Recommendations​

Purpose: Get intelligent static site generator recommendations based on your project.

Example Prompts:

  • "Recommend a static site generator for my TypeScript project"
  • "Which SSG works best with my Python documentation?"
  • "Compare documentation tools for my project"

What it returns: Weighted recommendations with justifications for Jekyll, Hugo, Docusaurus, MkDocs, or Eleventy.

3. Configuration Generation​

Purpose: Generate SSG-specific configuration files.

Example Prompts:

  • "Generate a Hugo config for my project"
  • "Create MkDocs configuration files"
  • "Set up Docusaurus for my documentation"

What it returns: Ready-to-use configuration files optimized for your project.

4. Documentation Structure​

Purpose: Create Diataxis-compliant documentation structure.

Example Prompts:

  • "Set up documentation structure following Diataxis"
  • "Create organized docs folders for my project"
  • "Build a comprehensive documentation layout"

What it returns: Organized folder structure with templates following documentation best practices.

5. GitHub Pages Deployment​

Purpose: Automate GitHub Pages deployment workflows.

Example Prompts:

  • "Deploy my docs to GitHub Pages"
  • "Set up automated documentation deployment"
  • "Create GitHub Actions for my documentation site"

What it returns: GitHub Actions workflows configured for your chosen SSG.

6. Deployment Verification​

Purpose: Verify and troubleshoot GitHub Pages deployments.

Example Prompts:

  • "Check if my GitHub Pages deployment is working"
  • "Troubleshoot my documentation deployment"
  • "Verify my docs site is live"

What it returns: Deployment status and troubleshooting recommendations.

Advanced Prompting Techniques​

Chained Operations​

You can chain multiple operations in a single conversation:

1. First analyze my repository
2. Then recommend the best SSG
3. Finally set up the deployment workflow

Specific Requirements​

Be specific about your needs:

I need a documentation site that:
- Works with TypeScript
- Supports API documentation
- Has good search functionality
- Deploys automatically on commits

Context-Aware Requests​

Reference previous analysis:

Based on the analysis you just did, create the documentation structure and deploy it to GitHub Pages

Best Practices​

1. Start with Analysis​

Always begin with repository analysis to get tailored recommendations:

analyze my project for documentation needs

2. Be Specific About Goals​

Tell DocuMCP what you're trying to achieve:

  • "I need developer documentation for my API"
  • "I want user guides for my application"
  • "I need project documentation for contributors"

3. Specify Constraints​

Mention any limitations or preferences:

  • "I prefer minimal setup"
  • "I need something that works with our CI/CD pipeline"
  • "I want to use our existing design system"

4. Ask for Explanations​

Request reasoning behind recommendations:

why did you recommend Hugo over Jekyll for my project?

5. Iterate and Refine​

Use follow-up prompts to refine results:

can you modify the GitHub Actions workflow to also run tests?

Common Workflows​

Complete Documentation Setup​

1. "Analyze my repository for documentation needs"
2. "Recommend the best static site generator for my project"
3. "Generate configuration files for the recommended SSG"
4. "Set up Diataxis-compliant documentation structure"
5. "Deploy everything to GitHub Pages"

Documentation Audit​

1. "Analyze my existing documentation"
2. "What gaps do you see in my current docs?"
3. "How can I improve my documentation structure?"

Deployment Troubleshooting​

1. "My GitHub Pages site isn't working"
2. "Check my deployment configuration"
3. "Help me fix the build errors"

Memory and Context​

DocuMCP remembers context within a conversation, so you can:

  • Reference previous analysis results
  • Build on earlier recommendations
  • Chain operations together seamlessly

Example conversation flow:

User: "analyze my repository"
DocuMCP: [provides analysis]
User: "based on that analysis, what SSG do you recommend?"
DocuMCP: [provides recommendation using analysis context]
User: "set it up with that recommendation"
DocuMCP: [configures the recommended SSG]

Troubleshooting Prompts​

If you're not getting the results you expect, try:

More Specific Prompts​

Instead of: "help with docs" Try: "analyze my TypeScript project and recommend documentation tools"

Context Setting​

Instead of: "set up deployment" Try: "set up GitHub Pages deployment for the MkDocs site we just configured"

Direct Tool Requests​

If you know exactly what you want:

  • "use the analyze_repository tool on my current directory"
  • "run the recommend_ssg tool with my project data"

Getting Help​

If you need assistance with prompting:

  • Ask DocuMCP to explain available tools: "what can you help me with?"
  • Request examples: "show me example prompts for documentation setup"
  • Ask for clarification: "I don't understand the recommendation, can you explain?"

Remember: DocuMCP is designed to understand natural language, so don't hesitate to ask questions in your own words!