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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
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

OLLAMA_URL
Optional
string

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

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

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

EMBEDDING_MODEL
Optional
string

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

EMBEDDING_PROVIDER
Optional
string

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

Default: ollama

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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