How to integrate Prisma MCP with Autogen

This guide walks you through connecting Prisma to AutoGen using the Composio tool router. By the end, you'll have a working Prisma agent that can create a new postgres database in your project, run a sql query to list all users, delete a database connection by name through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Prisma account through Composio's Prisma MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Prisma Data Platform is a suite of database tools for managing workspaces, projects, and PostgreSQL environments. It simplifies data access, query optimization, and secure platform automation.

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Introduction

This guide walks you through connecting Prisma to AutoGen using the Composio tool router. By the end, you'll have a working Prisma agent that can create a new postgres database in your project, run a sql query to list all users, delete a database connection by name through natural language commands.

This guide will help you understand how to give your AutoGen agent real control over a Prisma account through Composio's Prisma MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Prisma with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the required dependencies for Autogen and Composio
  • Initialize Composio and create a Tool Router session for Prisma
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Prisma tools
  • Run a live chat loop where you ask the agent to perform Prisma operations

What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.

Key features include:

  • Multi-Agent Systems: Build collaborative agent workflows
  • MCP Workbench: Native support for Model Context Protocol tools
  • Streaming HTTP: Connect to external services through streamable HTTP
  • AssistantAgent: Pre-built agent class for tool-using assistants

What is the Prisma MCP server, and what's possible with it?

The Prisma MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Prisma account. It provides structured and secure access to your database management, so your agent can perform actions like creating projects, managing databases, executing SQL queries, and handling API keys on your behalf.

  • Automated project and database provisioning: Instantly create new Prisma projects and managed PostgreSQL databases in your workspace, complete with connection strings and API keys for fast onboarding.
  • On-demand SQL execution and analysis: Have your agent run SQL commands or select queries for reporting, data inspection, or schema changes—without manual intervention.
  • API key and connection management: Programmatically generate, rotate, or revoke database API keys, ensuring secure and controlled access for all your applications.
  • Workspace and resource monitoring: Retrieve detailed information about your workspaces, projects, and databases, allowing your agent to validate deployments or monitor status in real time.
  • Safe resource cleanup and deletion: Direct your agent to delete databases, projects, or specific connections—helping you maintain a tidy, secure, and cost-effective data platform.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step08 STEPS
1

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Prisma account you can connect to Composio
  • Some basic familiarity with Autogen and Python async
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Prisma via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

4

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

Create a .env file in your project folder.

What's happening:

  • COMPOSIO_API_KEY is required to talk to Composio
  • OPENAI_API_KEY is used by Autogen's OpenAI client
  • USER_ID is how Composio identifies which user's Prisma connections to use
5

Import dependencies and create Tool Router session

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Prisma session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["prisma"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Prisma tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to
6

Configure MCP parameters for Autogen

python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.

What's happening:

  • url points to the Tool Router MCP endpoint from Composio
  • timeout is the HTTP timeout for requests
  • sse_read_timeout controls how long to wait when streaming responses
  • terminate_on_close=True cleans up the MCP server process when the workbench is closed
7

Create the model client and agent

python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Prisma assistant agent with MCP tools
    agent = AssistantAgent(
        name="prisma_assistant",
        description="An AI assistant that helps with Prisma operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Prisma tools from the workbench
8

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Prisma related question or task to the agent.\n")

# Conversation loop
while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    print("\nAgent is thinking...\n")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Prisma tools to call via MCP
  • agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
  • Typing exit, quit, or bye ends the loop

Complete Code

Here's the complete code to get you started with Prisma and AutoGen:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Prisma session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["prisma"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Prisma assistant agent with MCP tools
        agent = AssistantAgent(
            name="prisma_assistant",
            description="An AI assistant that helps with Prisma operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
        print("Ask any Prisma related question or task to the agent.\n")

        # Conversation loop
        while True:
            user_input = input("You: ").strip()

            if user_input.lower() in ['exit', 'quit', 'bye']:
                print("\nGoodbye!")
                break

            if not user_input:
                continue

            print("\nAgent is thinking...\n")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

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

Conclusion

You now have an Autogen assistant wired into Prisma through Composio's Tool Router and MCP. From here you can:
  • Add more toolkits to the toolkits list, for example notion or hubspot
  • Refine the agent description to point it at specific workflows
  • Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Prisma, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

Every Prisma action and event your agent gets out of the box.

Create Database Connection

Create new API key connection for database access.

Create Project Database

Create new postgres database in an existing Prisma project.

Create Prisma Project

Create new Prisma project with managed postgres database.

Delete Database Connection

Permanently delete database connection and revoke API key access.

Delete Prisma Database

Permanently delete Prisma database and all stored data.

Delete Prisma Project

Permanently delete Prisma project and all associated resources.

Execute SQL Command

Execute SQL commands that modify database data or structure.

Execute SQL Query

Execute SQL SELECT queries against Prisma Postgres databases.

Get Prisma Database

Retrieve specific Prisma database by ID.

Get Database Usage Metrics

Retrieve usage metrics for a specific Prisma database.

Get Prisma Project

Retrieve specific Prisma project by ID.

Inspect Database Schema

Inspect database schema structure and table information.

List Prisma Accelerate Regions

Retrieve all available regions for Prisma Accelerate.

List Database Backups

Retrieve list of available backups for a specific database.

List Database Connections

Retrieve paginated list of connections for a specific database.

List Project Databases

Retrieve paginated list of databases for a specific Prisma project.

List Prisma Postgres Regions

Retrieve all available regions for Prisma Postgres.

List Prisma Projects

Retrieve paginated list of Prisma projects accessible to authenticated user.

List Workspace Integrations

Retrieve paginated list of integrations for a specific Prisma workspace.

List Prisma Workspaces

Retrieve paginated list of Prisma workspaces accessible to authenticated user.

Restore Database Backup

Restore database backup to new database instance.

Transfer Prisma Project

Transfer Prisma project ownership to another user's workspace.

FRAMEWORKS

How to build Prisma MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Prisma MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Prisma MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Prisma MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Prisma MCP with Claude Cowork

Codex logo

Codex

Use Prisma MCP with Codex

OpenClaw logo

OpenClaw

Use Prisma MCP with OpenClaw

Hermes logo

Hermes

Use Prisma MCP with Hermes

CLI logo

CLI

Use Prisma MCP with CLI

Google ADK logo

Google ADK

Use Prisma MCP with Google ADK

LangChain logo

LangChain

Use Prisma MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Prisma MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Prisma MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Prisma MCP with LlamaIndex

CrewAI logo

CrewAI

Use Prisma MCP with CrewAI

FAQ

Frequently asked questions

With a standalone Prisma MCP server, the agents and LLMs can only access a fixed set of Prisma tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Prisma and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. Autogen fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Prisma tools.

Yes, absolutely. You can configure which Prisma scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Prisma data and credentials are handled as safely as possible.

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A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

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As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

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Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

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With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

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