Tools Combined
contextmore provides everything you need to build powerful RAG applications
Qdrant Integration
Seamlessly store and retrieve vector embeddings with Qdrant's powerful vector database.
FastAPI Backend
High-performance API endpoints for embedding generation and context retrieval.
MCP Integration
Connect to any AI application with Model Context Protocol support.
Custom Knowledge Base
Use your company's documentation, knowledge base, or any text data as context.
Fast Retrieval
Optimized for speed with efficient vector search and context retrieval.
RESTful API
Comprehensive API endpoints for easy integration with your existing applications and services.
How It Works
contextmore uses RAG to enhance AI responses with your own data
1. Index Your Data
Upload your company's documentation, knowledge base, or any text data. contextmore processes and indexes this information, creating vector embeddings stored in Qdrant.
2. Connect via MCP
Integrate contextmore with your AI applications using the Model Context Protocol. Simply add the MCP configuration to your project.
{
"mcpServers": {
"contextmore": {
"url": "http://localhost:8000/mcp"
}
}
}3. Retrieve Relevant Context
When a user asks a question, contextmore retrieves the most relevant information from your knowledge base using semantic search.
4. Generate Accurate Responses
The AI model uses the retrieved context to generate accurate, factual responses grounded in your data, minimizing hallucinations.
Benefits
Why companies and developers choose contextmore
Minimize Hallucinations
By grounding AI responses in your actual data, contextmore significantly reduces the risk of AI hallucinations and factual errors.
Up-to-date Information
Overcome LLM knowledge cutoffs by providing your AI with the latest information from your organization.
Proprietary Knowledge
Leverage your organization's unique knowledge and expertise in AI responses without exposing sensitive data.
Easy Integration
Simple integration with RESTful API and MCP makes it easy to add contextmore to your existing AI applications.
Scalable Architecture
Built on FastAPI and Qdrant, contextmore scales with your needs from small projects to enterprise applications.
Developer-Friendly
Designed with developers in mind, with clear documentation and simple APIs for quick implementation.