How to integrate Prisma MCP with CrewAI

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Introduction

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

This guide will help you understand how to give your CrewAI 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.

TL;DR

Here's what you'll learn:
  • Get a Composio API key and configure your Prisma connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Prisma
  • Build a conversational loop where your agent can execute Prisma operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

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.

Supported Tools & Triggers

Tools
Create Database ConnectionCreate new api key connection for database access.
Create Project DatabaseCreate new postgres database in an existing prisma project.
Create Prisma ProjectCreate new prisma project with managed postgres database.
Delete Database ConnectionPermanently delete database connection and revoke api key access.
Delete Prisma DatabasePermanently delete prisma database and all stored data.
Delete Prisma ProjectPermanently delete prisma project and all associated resources.
Execute SQL CommandExecute sql commands that modify database data or structure.
Execute SQL QueryExecute sql select queries against prisma databases.
Get Prisma DatabaseRetrieve specific prisma database by id.
Get Prisma ProjectRetrieve specific prisma project by id.
Inspect Database SchemaInspect database schema structure and table information.
List Prisma Accelerate RegionsRetrieve all available regions for prisma accelerate.
List Database BackupsRetrieve list of available backups for a specific database.
List Database ConnectionsRetrieve paginated list of connections for a specific database.
List Project DatabasesRetrieve paginated list of databases for a specific prisma project.
List Prisma Postgres RegionsRetrieve all available regions for prisma postgres.
List Prisma ProjectsRetrieve paginated list of prisma projects accessible to authenticated user.
List Prisma WorkspacesRetrieve paginated list of prisma workspaces accessible to authenticated user.
Restore Database BackupRestore database backup to new database instance.
Transfer Prisma ProjectTransfer prisma project ownership to another user.

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

What is Tool Router?

Composio's Tool Router 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 Tool Router

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

How the Tool Router works

The Tool Router 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

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Prisma connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python

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.

Install dependencies

bash
pip install composio crewai crewai-tools python-dotenv
What's happening:
  • composio connects your agent to Prisma via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools includes MCP helpers
  • python-dotenv loads environment variables from .env

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model

Import dependencies

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional import if you plan to adapt tools
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Prisma MCP URL

Create a Composio Tool Router session for Prisma

python
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:
  • You create a Prisma only session through Composio
  • Composio returns an MCP HTTP URL that exposes Prisma tools

Configure the LLM

python
llm = LLM(
    model="gpt-5-mini",
    api_key=os.getenv("OPENAI_API_KEY"),
)
What's happening:
  • CrewAI will call this LLM for planning and responses
  • You can swap in a different model if needed

Attach the MCP server and create the agent

python
toolkit_agent = Agent(
    role="Prisma Assistant",
    goal="Help users interact with Prisma through natural language commands",
    backstory=(
        "You are an expert assistant with access to Prisma tools. "
        "You can perform various Prisma operations on behalf of the user."
    ),
    mcps=[
        MCPServerHTTP(
            url=url,
            streamable=True,
            cache_tools_list=True,
            headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
        ),
    ],
    llm=llm,
    verbose=True,
    max_iter=10,
)
What's happening:
  • MCPServerHTTP connects the agent to the Prisma MCP endpoint
  • cache_tools_list saves a tools catalog for faster subsequent runs
  • verbose helps you see what the agent is doing

Add a REPL loop with Task and Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to perform Prisma operations.\n")

conversation_context = ""

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

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

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Based on the conversation history:\n{conversation_context}\n\n"
            f"Current user request: {user_input}\n\n"
            f"Please help the user with their Prisma related request."
        ),
        expected_output="A helpful response addressing the user's request",
        agent=toolkit_agent,
    )

    crew = Crew(
        agents=[toolkit_agent],
        tasks=[task],
        verbose=False,
    )

    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's happening:
  • You build a simple chat loop and keep a running context
  • Each user turn becomes a Task handled by the same agent
  • Crew executes the task and returns a response

Run the application

python
if __name__ == "__main__":
    main()
What's happening:
  • Standard Python entry point so you can run python crewai_prisma_agent.py

Complete Code

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

python
# file: crewai_prisma_agent.py
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()

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 LLM
    llm = LLM(
        model="gpt-5-mini",
        api_key=os.getenv("OPENAI_API_KEY"),
    )

    # Create Prisma assistant agent
    toolkit_agent = Agent(
        role="Prisma Assistant",
        goal="Help users interact with Prisma through natural language commands",
        backstory=(
            "You are an expert assistant with access to Prisma tools. "
            "You can perform various Prisma operations on behalf of the user."
        ),
        mcps=[
            MCPServerHTTP(
                url=url,
                streamable=True,
                cache_tools_list=True,
                headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
            ),
        ],
        llm=llm,
        verbose=True,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Try asking the agent to perform Prisma operations.\n")

    conversation_context = ""

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

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

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Based on the conversation history:\n{conversation_context}\n\n"
                f"Current user request: {user_input}\n\n"
                f"Please help the user with their Prisma related request."
            ),
            expected_output="A helpful response addressing the user's request",
            agent=toolkit_agent,
        )

        crew = Crew(
            agents=[toolkit_agent],
            tasks=[task],
            verbose=False,
        )

        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

if __name__ == "__main__":
    main()

Conclusion

You now have a CrewAI agent connected to Prisma through Composio's Tool Router. The agent can perform Prisma operations through natural language commands. Next steps:
  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations

How to build Prisma MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Prisma MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Prisma MCP with Claude Agent SDK

Google ADK

Google ADK

Use Prisma MCP with Google ADK

LangChain

LangChain

Use Prisma MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Prisma MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Prisma MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Prisma MCP with LlamaIndex

FAQ

What are the differences in Tool Router MCP and Prisma MCP?

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.

Can I use Tool Router MCP with CrewAI?

Yes, you can. CrewAI 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.

Can I manage the permissions and scopes for Prisma while using Tool Router?

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.

How safe is my data with Composio Tool Router?

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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