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MCP-Ragdocs

MCP-Ragdocs

Public
qpd-v/mcp-ragdocs

Enables semantic search and natural language retrieval of documentation by indexing content from URLs or local files into a vector database using Model Context Protocol integration.

javascript
0 tools
May 30, 2025
Updated Jun 4, 2025

Supercharge Your AI with MCP-Ragdocs

MCP Server

Unlock the full potential of MCP-Ragdocs through LangDB's AI Gateway. Get enterprise-grade security, analytics, and seamless integration with zero configuration.

Unified API Access
Complete Tracing
Instant Setup
Get Started Now

Free tier available • No credit card required

Instant Setup
99.9% Uptime
10,000+Monthly Requests
Configuration Requirements
API Key
Configure authentication and required variables to access this MCP server
Required Environment Variables
EMBEDDING_PROVIDER
Optional
string

Choose between 'ollama' (default) or 'openai' for the embedding provider.

Default: ollama
OLLAMA_URL
Optional
string

URL of your Ollama instance, defaults to http://localhost:11434.

Default: http://localhost:11434
OPENAI_API_KEY
Optional
string

Your OpenAI API key, required if using OpenAI as the embedding provider.

QDRANT_URL
Optional
string

URL of your Qdrant instance. For local use: http://localhost:6333. For Qdrant Cloud: https://your-cluster-url.qdrant.tech

EMBEDDING_MODEL
Optional
string

Optional embedding model. Defaults to 'nomic-embed-text' for Ollama and 'text-embedding-3-small' for OpenAI.

QDRANT_API_KEY
Optional
string

Your Qdrant Cloud API key, required if using Qdrant Cloud.

Security Notice

Your environment variables and credentials are securely stored and encrypted. LangDB never shares these configuration values with third parties.

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