ai-mldeveloper-tools

DocuMCP (RAG Documentation Server)

yannicktm

by yannicktm

DocuMCP: RAG documentation server with on-prem semantic search for code, docs, and diagrams — integrates vector DBs with

RAG-enabled documentation server that integrates with vector databases to provide semantic search capabilities for code, documentation, and diagrams without data leaving your environment.

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Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Data stays in your environmentMulti-agent orchestration for scaleMultiple vector database options

best for

  • / Developers maintaining large codebases
  • / Teams needing automated documentation workflows
  • / Enterprise applications requiring comprehensive docs
  • / Projects wanting semantic code search capabilities

capabilities

  • / Generate documentation from codebases automatically
  • / Search code and docs using semantic similarity
  • / Create and merge architectural diagrams
  • / Spawn multiple Claude agents for parallel processing
  • / Store embeddings in vector databases locally
  • / Track documentation generation costs and metrics

what it does

Generates intelligent documentation for codebases using RAG and semantic search, with optional multi-agent orchestration for large-scale documentation workflows.

about

DocuMCP (RAG Documentation Server) is a community-built MCP server published by yannicktm that provides AI assistants with tools and capabilities via the Model Context Protocol. DocuMCP: RAG documentation server with on-prem semantic search for code, docs, and diagrams — integrates vector DBs with It is categorized under ai ml, developer tools.

how to install

You can install DocuMCP (RAG Documentation Server) in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

DocuMCP (RAG Documentation Server) is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

DocuMCP

🤖 A comprehensive MCP system for intelligent code documentation generation with RAG capabilities and multi-agent orchestration

DocuMCP consists of two complementary MCP servers:

  1. DocuMCP Server: Core documentation generation with vector embeddings and semantic search
  2. DocuMCP Manager: Agent orchestration for parallel documentation workflows using multiple Claude Code sub-agents

Together, they enable Claude to generate, search, and manage documentation for your codebase at any scale, from single files to entire enterprise applications.

✨ Features

Core Documentation Features

  • 📚 Generate and update documentation based on your codebase
  • 🔍 Semantic search across code, documentation, and diagrams
  • 📊 Create and merge architectural diagrams
  • 📝 Generate user guides
  • 💾 Support for multiple vector databases (LanceDB, ChromaDB, Qdrant)
  • 🧠 Flexible embedding providers (built-in or Ollama)

Multi-Agent Orchestration (Manager Server)

  • 🤖 Spawn multiple Claude Code sub-agents for parallel processing
  • 📊 Monitor agent status and retrieve results
  • 🔄 Shared vector database across all agents
  • ⚡ Scale documentation generation for large codebases
  • 💰 Track costs and performance metrics

🚀 Quick Start

Installation via NPX (Recommended)

The easiest way to use DocuMCP is to configure Claude Desktop with the published npm package:

Add the following to your Claude Desktop configuration:

  • MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%/Claude/claude_desktop_config.json

For Core DocuMCP Server:

{
  "mcpServers": {
    "docu-mcp": {
      "command": "npx",
      "args": ["-y", "@myjungle/docu-mcp-server"]
    }
  }
}

For DocuMCP Manager (Agent Orchestration):

{
  "mcpServers": {
    "docu-mcp-manager": {
      "command": "npx",
      "args": ["-y", "@myjungle/docu-mcp-manager"]
    }
  }
}

Restart Claude Desktop and both servers will be available.

Alternative Installation Methods

Using Smithery CLI

Install the server via Smithery CLI:

# Install Smithery CLI if you don't have it
npm install -g @smithery/cli

# Then install the Docu MCP server
npx -y @smithery/cli@latest install @YannickTM/docu-mcp --client claude

🚀 Manual Start

1. Clone and Install

git clone https://github.com/YannickTM/docu-mcp
cd docu-mcp
npm install

2. Build the Servers

# Build DocuMCP Server
cd mcp
npm run build
cd ..

# Build DocuMCP Manager
cd manager
npm run build
cd ..

3. Advanced Configuration

Add the following to your Claude Desktop configuration:

  • MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%/Claude/claude_desktop_config.json

Configuration for Both Servers:

{
  "mcpServers": {
    "docu-mcp": {
      "command": "node",
      "env": {
        "VECTOR_DB_PROVIDER": "qdrant",
        "QDRANT_URL": "http://localhost:6333",
        "EMBEDDING_PROVIDER": "ollama",
        "EMBEDDING_MODEL": "bge-m3:latest",
        "EMBEDDING_DIMENSION": "1024",
        "OLLAMA_URL": "http://localhost:11434"
      },
      "args": ["/absolute/path/to/DocuMCP/mcp/dist/index.js"]
    },
    "docu-mcp-manager": {
      "command": "node",
      "env": {
        "VECTOR_DB_PROVIDER": "qdrant",
        "QDRANT_URL": "http://localhost:6333",
        "EMBEDDING_PROVIDER": "ollama",
        "EMBEDDING_MODEL": "bge-m3:latest",
        "EMBEDDING_DIMENSION": "1024",
        "OLLAMA_URL": "http://localhost:11434",
        "SUB_AGENT_MODEL": "claude-3-7-sonnet-latest"
      },
      "args": ["/absolute/path/to/DocuMCP/manager/dist/index.js"]
    }
  }
}

Important: Both servers should use the same vector database configuration to enable shared access.

4. Start Required Services (if using external providers)

For Qdrant:

cd qdrant
npm run start

For ChromaDB:

cd chromadb
npm run start

5. Restart Claude Desktop

Restart Claude Desktop to load the new configuration.

🛠️ Configuration Options

Vector Database Providers

ProviderDescriptionConfiguration
LanceDBFile-based local database (default)VECTOR_DB_PROVIDER=lance<br/>LANCE_PATH=~/lanceDB
ChromaDBSimple vector database with web UIVECTOR_DB_PROVIDER=chroma<br/>CHROMA_URL=http://localhost:8000
QdrantProduction-grade vector databaseVECTOR_DB_PROVIDER=qdrant<br/>QDRANT_URL=http://localhost:6333

Embedding Providers

ProviderDescriptionConfiguration
Built-inUses all-MiniLM-L6-v2 model (default)EMBEDDING_PROVIDER=buildin<br/>EMBEDDING_MODEL=all-MiniLM-L6-v2<br/>EMBEDDING_DIMENSION=384
OllamaUse any Ollama modelEMBEDDING_PROVIDER=ollama<br/>EMBEDDING_MODEL=bge-m3:latest<br/>EMBEDDING_DIMENSION=1024<br/>OLLAMA_URL=http://localhost:11434

🔧 Available Tools

DocuMCP Server Tools

  • 📁 File Operations: read_file, write_file, create_directory, read_directory
  • 🔎 Search Tools: search_codebase, search_documentation, search_diagram, search_user_guide
  • 📚 Documentation: generate_documentation, generate_user_guide, explain_code
  • 📊 Diagrams: generate_diagram, merge_diagram
  • 🗃️ Indexing: index_file, index_directory
  • 🔀 Merging: merge_documentation

DocuMCP Manager Tools (includes all above plus):

  • 🤖 Agent Orchestration:
    • spawn_agent: Create Claude Code sub-agents for documentation tasks
    • manage_agent: Monitor, control, and retrieve results from agents

📋 Requirements

  • Node.js 20.11.24+
  • Claude Desktop
  • (Optional) Docker for running external vector databases

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.


Made with ❤️

FAQ

What is the DocuMCP (RAG Documentation Server) MCP server?
DocuMCP (RAG Documentation Server) is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for DocuMCP (RAG Documentation Server)?
This profile displays 57 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.657 reviews
  • Chaitanya Patil· Dec 24, 2024

    We wired DocuMCP (RAG Documentation Server) into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Kiara Yang· Dec 8, 2024

    We wired DocuMCP (RAG Documentation Server) into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Tariq Sharma· Dec 8, 2024

    DocuMCP (RAG Documentation Server) reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Kiara Martin· Nov 27, 2024

    DocuMCP (RAG Documentation Server) is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Ira Anderson· Nov 27, 2024

    Useful MCP listing: DocuMCP (RAG Documentation Server) is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Piyush G· Nov 15, 2024

    DocuMCP (RAG Documentation Server) is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Zara Verma· Nov 15, 2024

    DocuMCP (RAG Documentation Server) has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Aanya Rao· Oct 18, 2024

    DocuMCP (RAG Documentation Server) is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • William Thomas· Oct 18, 2024

    We evaluated DocuMCP (RAG Documentation Server) against two servers with overlapping tools; this profile had the clearer scope statement.

  • Shikha Mishra· Oct 6, 2024

    DocuMCP (RAG Documentation Server) is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

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