DocuMCP (RAG Documentation Server)▌
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.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
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:
- DocuMCP Server: Core documentation generation with vector embeddings and semantic search
- 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
| Provider | Description | Configuration |
|---|---|---|
| LanceDB | File-based local database (default) | VECTOR_DB_PROVIDER=lance<br/>LANCE_PATH=~/lanceDB |
| ChromaDB | Simple vector database with web UI | VECTOR_DB_PROVIDER=chroma<br/>CHROMA_URL=http://localhost:8000 |
| Qdrant | Production-grade vector database | VECTOR_DB_PROVIDER=qdrant<br/>QDRANT_URL=http://localhost:6333 |
Embedding Providers
| Provider | Description | Configuration |
|---|---|---|
| Built-in | Uses all-MiniLM-L6-v2 model (default) | EMBEDDING_PROVIDER=buildin<br/>EMBEDDING_MODEL=all-MiniLM-L6-v2<br/>EMBEDDING_DIMENSION=384 |
| Ollama | Use any Ollama model | EMBEDDING_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 tasksmanage_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.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 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
4.6★★★★★57 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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