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Condense MCP connects the AI tool you already use, such as Claude, Cursor or GitHub Copilot, to your Condense environment. You ask in plain language. The AI tool inspects your pipelines, reads connector configurations and logs, searches the Condense documentation for you, and can deploy a connector. It works as you, so it can only do what your Condense permissions already allow.
Model Context Protocol (MCP) is a standard way for an AI tool to discover and use the tools that another service offers. Condense MCP is the Condense side of that standard. You may also see an AI tool called an AI assistant or an MCP client.

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At a glance

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What you can do

See what is running

Get the pipeline in a workspace: its connectors, the connections between them and their resource usage.

Read connector configurations

See how a deployed connector is configured, or open a custom connector as an editable application.

Read connector logs

Collect the logs of a deployed connector for a time window you choose.

Deploy connectors

Find out which fields a prebuilt or custom connector needs, then deploy it with the configuration you give.

Ask the documentation

Ask how something works in Condense and get the most relevant sections back.

Find your workspaces

List the workspaces you can reach, or switch to the one you name.

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What it does not do

  • It cannot change much. Deploying a connector is the only change it can make. It has no tools to restart, scale or delete anything, so do those in Condense Core or Console.
  • It does not read metrics, alerts or Kafka topics. The nine tools cover workspaces, pipelines, connectors, connector logs and documentation. Use Condense Core and Console for metrics and alerts, and ask about the pipeline, its connectors and their logs instead of Kafka topics.
  • One connection reads one environment. To use another environment, connect again and choose it.
  • It cannot give you more access than you have. Your Condense permissions still apply to everything it does.

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Before you connect

You need:
  • An active Condense account in the organization you want to use.
  • Membership of the environment and workspace you want to work with, with the permissions you need there.
  • An AI tool that supports remote MCP servers and the OAuth sign-in that Condense uses.
  • A browser that can complete the sign-in and the approval.
  • To deploy a connector, the connector’s configuration values and a role that lets you deploy in that workspace.

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How access is decided

Three things decide what your AI tool can do, and the narrowest one wins.
  • What you approve. When you connect, you choose one environment and which tools the AI tool may use. You can change this later from the AI Tools page.
  • What your administrator allows. An Organization Admin sets the allowed permissions and the operating mode for each environment in AI Governance.
  • What your Condense role allows. The AI tool inherits your permissions. It can do nothing in Condense that you could not do yourself.
Access also follows the way Condense is organized.
Approving a connection never gives you anything new. If your AI tool cannot read something, the fix is a role from your administrator, not a change to a setting on your side.

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Next steps

Quickstart

Connect and ask your first question in a few minutes.

Connect your AI tool

Setup for Claude Code, Claude Desktop, Cursor, GitHub Copilot, Gemini CLI and Codex.

Tool reference

The nine tools and what each one needs.