Use Agno to Talk to Your AlloyDB Data via CData Connect AI

Agno is a developer-first Python framework for building AI agents that reason, plan, and take actions using tools. Agno emphasizes a clean, code-driven architecture where the agent runtime remains fully under developer control.

CData Connect AI provides a secure cloud-to-cloud interface for integrating 300+ enterprise data sources with AI systems. Using Connect AI, live AlloyDB data data can be exposed through a remote MCP endpoint without replication.

In this guide, we build a production-ready Agno agent using the Agno Python SDK. The agent connects to CData Connect AI via MCP using streamable HTTP, dynamically discovers available tools, and invokes them to query live AlloyDB data.

Prerequisites

1. Python 3.9+.
2. A CData Connect AI account – Sign up or log in here.
3. An active AlloyDB account with valid credentials.
4. An LLM API key (for example, OpenAI).

Overview

Here is a high-level overview of the process:

1. Connect: Configure a AlloyDB connection in CData Connect AI.
2. Discover: Use MCP to dynamically retrieve tools exposed by CData Connect AI.
3. Query: Wrap MCP tools as Agno functions and query live AlloyDB data.

Step 1: Configure AlloyDB in CData Connect AI

To enable Agno to query live AlloyDB data, first create a AlloyDB connection in CData Connect AI. This connection is exposed through the CData Remote MCP Server.

1. Log into Connect AI, click Sources, and then click Add Connection.
2. Select "AlloyDB" from the Add Connection panel.
3. Enter the required authentication properties.

   The following connection properties are usually required in order to connect to AlloyDB.

   • Server: The host name or IP of the server hosting the AlloyDB database.
   • User: The user which will be used to authenticate with the AlloyDB server.
   • Password: The password which will be used to authenticate with the AlloyDB server.

   You can also optionally set the following:

   • Database: The database to connect to when connecting to the AlloyDB Server. If this is not set, the user's default database will be used.
   • Port: The port of the server hosting the AlloyDB database. This property is set to 5432 by default.

   Authenticating with Standard Authentication

   Standard authentication (using the user/password combination supplied earlier) is the default form of authentication.

   No further action is required to leverage Standard Authentication to connect.

   Authenticating with pg_hba.conf Auth Schemes

   There are additional methods of authentication available which must be enabled in the pg_hba.conf file on the AlloyDB server.

   Find instructions about authentication setup on the AlloyDB Server here.

   Authenticating with MD5 Authentication

   This authentication method must be enabled by setting the auth-method in the pg_hba.conf file to md5.

   Authenticating with SASL Authentication

   This authentication method must be enabled by setting the auth-method in the pg_hba.conf file to scram-sha-256.

   Authenticating with Kerberos

   The authentication with Kerberos is initiated by AlloyDB Server when the ∏ is trying to connect to it. You should set up Kerberos on the AlloyDB Server to activate this authentication method. Once you have Kerberos authentication set up on the AlloyDB Server, see the Kerberos section of the help documentation for details on how to authenticate with Kerberos. Click Create & Test.

4. Open the Permissions tab and configure user access.

Add a Personal Access Token

A Personal Access Token (PAT) authenticates MCP requests from Agno to CData Connect AI.

1. Open Settings and navigate to Access Tokens.
2. Click Create PAT.
3. Save the generated token securely.

Step 2: Install dependencies and configure environment variables

Install Agno and the MCP adapter dependencies. LangChain is included strictly for MCP tool compatibility.

pip install agno agno-mcp langchain-mcp-adapters

Configure environment variables:

export CDATA_MCP_URL="https://mcp.cloud.cdata.com/mcp"
export CDATA_MCP_AUTH="Base64EncodedCredentials"
export OPENAI_API_KEY="your-openai-key"

Where "Base64EncodedCredentials" is your Connect AI user email and your Personal Access Token joined by a colon (":") and Base64 Encoded: Base64([email protected]:MY_CONNECT_AI_PAT)

Step 3: Connect to CData Connect AI via MCP

Create an MCP client using streamable HTTP. This establishes a secure connection to CData Connect AI.

import os
from langchain_mcp_adapters.client import MultiServerMCPClient

mcp_client = MultiServerMCPClient(
  connections={
    "default": {
      "transport": "streamable_http",
      "url": os.environ["CDATA_MCP_URL"],
      "headers": {
        "Authorization": f"Basic {os.environ['CDATA_MCP_AUTH']}"
      }
    }
  }
)

Step 4: Discover MCP tools

CData Connect AI exposes operations as MCP tools. These are retrieved dynamically at runtime.

langchain_tools = await mcp_client.get_tools()
for tool in langchain_tools:
  print(tool.name)

Step 5: Convert MCP tools to Agno functions

Each MCP tool is wrapped as an Agno function so it can be used by the agent.

NOTE: Agno performs all reasoning, planning, and tool selection.LangChain is used only as a lightweight MCP compatibility layer to consume tools exposed by CData Connect AI.

from agno.tools import Function

def make_tool_caller(lc_tool):
  async def call_tool(**kwargs):
    return await lc_tool.ainvoke(kwargs)
  return call_tool

Step 6: Create an Agno agent and query live AlloyDB data

Agno performs all reasoning, planning, and tool invocation. LangChain plays no role beyond MCP compatibility.

from agno.agent import Agent
from agno.models.openai import OpenAIChat

agent = Agent(
  model=OpenAIChat(
    id="gpt-4o",
    temperature=0.2,
    api_key=os.environ["OPENAI_API_KEY"]
  ),
  tools=agno_tools,
  markdown=True
)

await agent.aprint_response(
  "Show me the top 5 records from the available data source"
)

if __name__ == "__main__":
    asyncio.run(main())

The results below show an Agno agent invoking MCP tools through CData Connect AI and returning live AlloyDB data data.

You can now query live AlloyDB data using natural language through your Agno agent.

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