The World’s First Context-Aware MCP Server.
Build agents that choose the right tool every time, retrieving from your knowledge base naturally and delivering smarter results with Ragie’s Context-Aware MCP Server.
Smarter Routing with Context-Aware Descriptions
Generic tool descriptions leave LLMs guessing, often defaulting to web search. Ragie MCP Server generates context-aware descriptions that give LLMs high confidence to pick the retrieval tool and access the right knowledge. Watch the demo below to see the difference.
How teams use Ragie's MCP Server
Ragie MCP plugs into any MCP workflow. Here’s how developers and teams use it.
book a demo to explore
Cursor & Claude Desktop
Query your knowledge base directly from your editor with minimal setup.
Agent Frameworks
Let agents retrieve precise, up-to-date context across all your sources.
Enterprise Copilots
Power enterprise copilots with full knowledge base access and smart routing.
Custom Developer Tools
Add Ragie MCP to any workflow with a few lines of config.
Built for developers
Built for production from day one, Ragie MCP delivers the flexibility and control developers need.
Context-aware descriptions
Dynamic retrieval tool descriptions evolve with your content so agents route correctly.
Easy setup
Connect Ragie’s hosted MCP server with a single API key. No infrastructure to manage.
Control what gets retrieved
Fine-tune output with filters like top-k, rerank, and recency bias. No over-fetching or noise.
Secure access with partition control
Scope queries to specific teams, tenants, or knowledge domains for precise access control.
Plug-and-play with developer tools
Works with MCP-compatible clients like Cursor and Goose, with more client support coming soon.
Context-aware, open sourced
Ragie's open-sourced FastMCP project lets you extend your own MCP servers with dynamic, context-aware tool descriptions.
view github repo
Give your agents access to your knowledge base instantly
Copy the server entry URL from your partition, paste it into your MCP client, and start retrieving with no setup or infrastructure required. Read the docs.
