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The Omni MCP Server enables natural language querying across your datasets, similar to how you’d interact with Omni, while taking advantage of the enhanced context, reasoning, or memory capabilities of external AI tools. For example, you could include the results of a web search as additional context to the MCP before running an Omni query. MCP Server in Cursor

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Features

  • Natural language querying – Ask questions using natural language and let Omni translate it into a query
  • Iterative, multi-step analysis – Chain queries together, retain results in memory, and perform deeper analysis across steps
  • Flexible integration - Connect to a variety of compatible AI clients to expand beyond Omni’s native chat experience
  • Dynamic model selection - Switch between Omni models during a session without reconfiguring the MCP Server
  • Scoped, secure data access – Interactions are scoped only to the model (and topic, if provided) provided to the MCP, preventing unauthorized data access when querying
  • User level permissioning - MCP queries can be scoped to the permissions of a given user to pass through security from Omni’s semantic layer

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Tools

When you send a query to the MCP Server, it uses the following tools to process your request:
  1. pickModel - Returns a list of available models and their IDs. The MCP client uses this to select which model to query. You can also provide a model ID in the configuration to skip this step.
  2. pickTopic - Once a model is selected, this tool returns the available topics within that model. The MCP client selects the most relevant topic for your query.
  3. getData - Executes the query against the selected model and topic, returning the results.
This dynamic selection flow allows you to switch between models during a session without needing to reconfigure the MCP Server.

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Quickstart

Ready to get started? Check out the Quickstart or the guides for the clients we’ve tested for compatiblity:

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Improving results

To get the best results, we recommend:
  1. Optimizing your Omni models for AI. Refer to this guide to learn how to curate your models and include context.
  2. Rating the results that the AI returns

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Data access and security

  • Data access - Interactions are scoped only to the model (and topic, if provided) provided to the MCP, preventing unauthorized data access when querying
  • Data handling & security - Data returned from queries run by the MCP is handled the same way it is for Omni’s other AI features. Note: By using the MCP Server, your data will be in the tool where you use the MCP Server. For example, if you use Cursor with the MCP Server, your data would be in Cursor.