Connect to LlamaIndex

You can connect your LlamaIndex data sources to TypingMind to look up and query information directly from your own data. This integration uses MCP (Model Context Protocol) to act as a bridge between TypingMind and LlamaIndex.

What is LlamaIndex?

LlamaIndex is a data framework that lets you connect AI models to your private or organizational data. By creating an index, you can structure and retrieve information from multiple data sources such as documents, databases, or APIs.

When connected to TypingMind, you can ask questions and run deep research across your own indexed data.

How to set up LlamaIndex on TypingMind

You can connect LlamaIndex on TypingMind using MCP server.

Step 1: Create an Index in LlamaIndex

Sign up for a LlamaIndex account (if you don’t already have one).

Go to Index and create a new index.

Connect your index to your data sources (e.g., Google Drive, Notion, databases, here are the details)

Once created, note down your:

Index name

Project name

Organization ID

👉 If you already have an index, click into it to review its details and data source connections.

Step 2: Get your LlamaIndex API Key

Go to API Keys

Generate New Key

Step 3: Set up MCP Connectors on TypingMind

In TypingMind, go to Settings → Advanced Settings → Model Context Protocol to start setup your MCP connector. The MCP Connector acts as the bridge between TypingMind and the MCP servers.

MCP servers require a server to run on. TypingMind allows you to connect to the MCP servers via:

Your own local device

Or a private remote server.

If you choose to run the MCP servers on your device, run the command displayed on the screen.

Detail setup can be found at https://docs.typingmind.com/model-context-protocol-in-typingmind

Step 4: Configure LlamaCloud MCP on TypingMind

Add the following JSON configuration under MCP Servers in TypingMind settings:

json
{
  "mcpServers": {
    "llamacloud": {
      "command": "npx",
      "args": [
        "-y",
        "@llamaindex/mcp-server-llamacloud",
        "--index",
        "<your-index-name>",
        "--description",
        "<your-index-description>",
        "--topK",
        "5",
        "--index",
        "<your-another-index-name>",
        "--description",
        "<your-another-index-description>"
      ],
      "env": {
        "LLAMA_CLOUD_API_KEY": "<YOUR_API_KEY>",
        "LLAMA_CLOUD_ORG_ID": "<organization_ID>",
        "LLAMA_CLOUD_PROJECT": "<project_name>"
      }
    }
  }
}

Replace <your-index-name> and <your-index-description> with your actual index details in step 1.

You can add multiple indexes by repeating the -index and -description arguments.

Replace <YOUR_API_KEY> with your Llama Cloud API key in step 2.

You can also optionally specify --topK to limit the number of results.

The LLAMA_CLOUD_PROJECT_NAME environment variable is optional and defaults to Default if not set.

More information about LlamaCloud MCP

Step 5: Enable and Use LlamaIndex in TypingMind

After saving your MCP configuration:

Enable LlamaCloud plugin in TypingMind.

Start asking questions and running research directly on your indexed data.