Summary
Domain questions answered from your documents, with the sources shown.
The part worth spending time on is not the install but the description you write for the agent: that is what decides when your client reaches for it instead of answering from memory. If running one is not appealing, the platform hosts a server whose query tool behaves the same way.
What it is
A server that sits between an MCP client and a Contextual AI agent: the question goes to the agent you nominate, the agent searches your datastore, and the answer comes back grounded in what it found.
What you get
- Answers drawn from your knowledge base rather than from model training
- Citations and attributions alongside each answer
- Conversation context carried across turns, so a follow-up does not need the question restated
- A hosted server inside the platform, if you would rather not run one
- A server you configure yourself, including the description that tells the client when a question belongs to it
Requirements
Python 3.10 or higher and a Contextual AI API key. The server hosted inside the platform needs neither — connect to it and use the tools it offers.