Skip to main content

​
Prerequisites

Before you can configure and use LlamaIndex with Connect AI, you must do the following:
  • Connect a data source to your Connect AI account. See Sources for more information.
  • Generate an OAuth JWT bearer token. Copy this down, as it acts as your password during authentication.
  • Obtain an OpenAI API key: https://platform.openai.com.
  • Make sure you have Python >= 3.10 in order to install the LlamaIndex packages.

​
Create the Python Files

1
Create a folder for LlamaIndex MCP.
2
Create a Python file within the folder called llamaindex.py.
3
In llamaindex.py, set up your MCP server and MCP client to call the tools and prompts. The Authorization is Bearer and the JWT bearer token from the prerequisites.
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, aget_tools_from_mcp_url
from llama_index.core.agent import ReActAgent
import asyncio

client = BasicMCPClient(
    "https://mcp.cloud.cdata.com/mcp",
    headers={"Authorization": "Bearer OAUTH_JWT_TOKEN"}
)

async def main():
    # List available tools
    tools = await aget_tools_from_mcp_url("https://mcp.cloud.cdata.com/mcp", client=client)
   
    llm = OpenAI(model="gpt-4o", api_key="YOUR_OPENAI_KEY")   
    # Create ReActAgent
    agent = ReActAgent(tools=tools, llm=llm, verbose=True)
    # # Run a query
    response = await agent.run("List all the catalogs for me please")
    print(response)

asyncio.run(main())

​
Install the LlamaIndex Packages

Run the following command in your project terminal: 
pip install llama-index llama-index-llms-openai llama-index-tools-mcp

​
Run the Python Script

1
When the installation finishes, run the following command to execute the script:
python llamaindex.py
2
The script discovers the Connect AI MCP tools needed for the LLM to query the connected data.
3
Supply a prompt for the agent. The agent provides a response.
LlamaIndex Client Terminal