MCP-Ragdocs
A Model Context Protocol (MCP) server that enables semantic search and retrieval of documentation using a vector database (Qdrant). This server allows you to add documentation from URLs or local files and then search through them using natural language queries.
Quick Install Guide
Install the package globally:
npm install -g @qpd-v/mcp-server-ragdocsStart Qdrant (using Docker):
docker run -p 6333:6333 -p 6334:6334 qdrant/qdrantEnsure Ollama is running with the default embedding model:
ollama pull nomic-embed-textAdd to your configuration file:
For Cline:
%AppData%\Roaming\Code\User\globalStorage\saoudrizwan.claude-dev\settings\cline_mcp_settings.json
For Roo-Code:
%AppData%\Roaming\Code\User\globalStorage\rooveterinaryinc.roo-cline\settings\cline_mcp_settings.json
For Claude Desktop:
%AppData%\Claude\claude_desktop_config.json
{ "mcpServers": { "ragdocs": { "command": "node", "args": ["C:/Users/YOUR_USERNAME/AppData/Roaming/npm/node_modules/@qpd-v/mcp-server-ragdocs/build/index.js"], "env": { "QDRANT_URL": "http://127.0.0.1:6333", "EMBEDDING_PROVIDER": "ollama", "OLLAMA_URL": "http://localhost:11434" } } } }Verify installation:
# Check Qdrant is running curl http://localhost:6333/collections # Check Ollama has the model ollama list | grep nomic-embed-text
Version
Current version: 0.1.6
Features
Add documentation from URLs or local files
Store documentation in a vector database for semantic search
Search through documentation using natural language
List all documentation sources
Installation
Install globally using npm:
This will install the server in your global npm directory, which you'll need for the configuration steps below.
Requirements
Node.js 16 or higher
Qdrant (either local or cloud)
One of the following for embeddings:
Ollama running locally (default, free)
OpenAI API key (optional, paid)
Qdrant Setup Options
Option 1: Local Qdrant
Using Docker (recommended):
Or download from Qdrant's website
Option 2: Qdrant Cloud
Create an account at Qdrant Cloud
Create a new cluster
Get your cluster URL and API key from the dashboard
Use these in your configuration (see Configuration section below)
Configuration
The server can be used with both Cline/Roo and Claude Desktop. Configuration differs slightly between them:
Cline Configuration
Add to your Cline settings file (%AppData%\Roaming\Code\User\globalStorage\saoudrizwan.claude-dev\settings\cline_mcp_settings.json
)
AND/OR
Add to your Roo-Code settings file (%AppData%\Roaming\Code\User\globalStorage\rooveterinaryinc.roo-cline\settings\cline_mcp_settings.json
):
Using npm global install (recommended):
For OpenAI instead of Ollama:
Using local development setup:
Claude Desktop Configuration
Add to your Claude Desktop config file:
Windows:
%AppData%\Claude\claude_desktop_config.json
macOS:
~/Library/Application Support/Claude/claude_desktop_config.json
Windows Setup with Ollama (using full paths):
Windows Setup with OpenAI:
macOS Setup with Ollama:
Qdrant Cloud Configuration
For either Cline or Claude Desktop, when using Qdrant Cloud, modify the env section:
With Ollama:
With OpenAI:
Environment Variables
Qdrant Configuration
QDRANT_URL
(required): URL of your Qdrant instanceFor local: http://localhost:6333
For cloud: https://your-cluster-url.qdrant.tech
QDRANT_API_KEY
(required for cloud): Your Qdrant Cloud API key
Embeddings Configuration
EMBEDDING_PROVIDER
(optional): Choose between 'ollama' (default) or 'openai'EMBEDDING_MODEL
(optional):For Ollama: defaults to 'nomic-embed-text'
For OpenAI: defaults to 'text-embedding-3-small'
OLLAMA_URL
(optional): URL of your Ollama instance (defaults to http://localhost:11434)OPENAI_API_KEY
(required if using OpenAI): Your OpenAI API key
Available Tools
add_documentation
Add documentation from a URL to the RAG database
Parameters:
url
: URL of the documentation to fetch
search_documentation
Search through stored documentation
Parameters:
query
: Search querylimit
(optional): Maximum number of results to return (default: 5)
list_sources
List all documentation sources currently stored
No parameters required
Example Usage
In Claude Desktop or any other MCP-compatible client:
Add documentation:
Search documentation:
List sources:
Development
Clone the repository:
Install dependencies:
Build the project:
Run locally:
License
MIT
Troubleshooting
Common Issues
Qdrant Connection Error
Error: Failed to connect to Qdrant at http://localhost:6333Check if Docker is running
Verify Qdrant container is running:
docker ps | grep qdrant
Try restarting the container
Ollama Model Missing
Error: Model nomic-embed-text not foundRun:
ollama pull nomic-embed-text
Verify model is installed:
ollama list
Configuration Path Issues
Windows: Replace
YOUR_USERNAME
with your actual Windows usernameCheck file permissions
Verify the paths exist
npm Global Install Issues
Try installing with admin privileges
Check npm is in PATH:
npm -v
Verify global installation:
npm list -g @qpd-v/mcp-server-ragdocs
For other issues, please check:
Docker logs:
docker logs $(docker ps -q --filter ancestor=qdrant/qdrant)
Ollama status:
ollama list
Node.js version:
node -v
(should be 16 or higher)
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
This server cannot be installed
hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
A Model Context Protocol (MCP) server that enables semantic search and retrieval of documentation using a vector database (Qdrant). This server allows you to add documentation from URLs or local files and then search through them using natural language queries.
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