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Set up Invero with your agent

Your agent connects a knowledge source to Invero, checks that its content is searchable, and helps you put it to use. If you prefer to go through each step yourself, follow Index a source in the dashboard instead.

By the end of this tutorial, you will have:

  • A knowledge source in your Invero project, with its content searchable.
  • A real query returning results from that content.
  • Optionally, your knowledge deployed, for example as a Website Widget or a Slack Bot.

Before you start​

You need:

  • A Invero account, or create one when the agent asks.
  • Permission to edit the project's sources and integrations.
  • An agent: Claude Code, Codex, Cursor, Gemini CLI, or opencode, or a chat assistant such as ChatGPT or Claude.
  • Access to the source you want to connect, such as a Confluence token.

Most of the supported data sources can be set up this way, including web crawling, GitHub, Zendesk, Confluence, Jira, Notion, Slack, Discord, Google Drive, and S3. Set up the rest in the dashboard.

Copy the prompt​

Paste this prompt into your agent. It handles installation, source configuration, ingestion checks, and a test query, asking you for sign-in, source access, and any choices it needs.

ChatGPT and Claude cannot install the plugin themselves. Connect Invero first, as described in If your agent needs help connecting, then paste the prompt.

Agent prompt

Answer the agent's questions​

From here, the agent leads, and you answer. This section walks through what it asks at each stage, so you know what to have ready.

Sign in to the MCP server​

The agent installs the Invero plugin if it is not connected yet, sends you to sign up if you have no account, and then checks that you are signed in to the Invero platform MCP server, so it can reach the platform on your behalf. If you are not, it tells you how to sign in. If you have more than one project, it asks which one to set up, and it tells you what that project already holds before it changes anything.

Choose what to ingest​

Next, the agent lists what Invero can ingest and asks what you want to start with. Reply with the source, like the URL of your documentation site.

The agent listing the source types Invero can ingest and asking which one to start with

Wait for your source to ingest​

The agent then works out the source's configuration with you, such as which pages to crawl, and starts ingesting once you give it the go-ahead. Ingestion usually takes a couple of minutes.

To follow its progress, ask the agent for the status of your source, including how many items are already deployed. Or open app.invero.ai and navigate to Sources (under Configure in the sidebar): the source row shows the deployed count ticking up, and the spinner disappears once ingestion is finished.

Source row showing the deployed page count with a spinner while some updates are still being deployed

Test your index with a few queries​

Next, you test searching the source you just indexed. The agent asks you for a question your content should answer, or suggests one, and shows you the chunks that come back and the source of each one. Ask a few more questions to check other parts of your content.

The platform MCP server lets your agent search with the same retrieval tool that the hosted MCP server and the HTTP API expose, which are how you usually query your index in production.

If the results are thin or wrong, the agent says so rather than declaring success, and points to the likely cause, usually a misconfigured source.

Deploy your index (optional)​

Finally, the agent asks whether you want to deploy your index. Deploying connects it to the places where it gets used: either a Prebuilt Agent, such as a website widget or a Slack bot, that answers your users directly, or a way for your own agents to query it, through a hosted MCP server or the HTTP API. You can pick more than one.

The agent asking how to deploy the project, with options for a website widget, an MCP server, a Slack or Discord bot, and building on the API

If your agent needs help connecting​

The prompt has your agent install the Invero plugin, which connects it to the Invero platform MCP server and teaches it how to set up each source type. Chat assistants cannot install it themselves, so connect Invero first, then paste the prompt. Use these steps if the agent gets stuck.

Inside Claude Code:

/plugin marketplace add invero-ai/invero-plugin
/plugin install invero@invero

Or from your terminal:

claude plugin marketplace add invero-ai/invero-plugin
claude plugin install invero@invero

Next steps​