# How to integrate Prisma MCP with LlamaIndex

```json
{
  "title": "How to integrate Prisma MCP with LlamaIndex",
  "toolkit": "Prisma",
  "toolkit_slug": "prisma",
  "framework": "LlamaIndex",
  "framework_slug": "llama-index",
  "url": "https://composio.dev/toolkits/prisma/framework/llama-index",
  "markdown_url": "https://composio.dev/toolkits/prisma/framework/llama-index.md",
  "updated_at": "2026-05-12T10:22:42.226Z"
}
```

## Introduction

This guide walks you through connecting Prisma to LlamaIndex 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 LlamaIndex 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 SDK](https://composio.dev/toolkits/prisma/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/prisma/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/prisma/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/prisma/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/prisma/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/prisma/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/prisma/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/prisma/framework/cli)
- [Google ADK](https://composio.dev/toolkits/prisma/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/prisma/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/prisma/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/prisma/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/prisma/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- Set your OpenAI and Composio API keys
- Install LlamaIndex and Composio packages
- Create a Composio Tool Router session for Prisma
- Connect LlamaIndex to the Prisma MCP server
- Build a Prisma-powered agent using LlamaIndex
- Interact with Prisma through natural language

## What is LlamaIndex?

LlamaIndex is a data framework for building LLM applications. It provides tools for connecting LLMs to external data sources and services through agents and tools.
Key features include:
- ReAct Agent: Reasoning and acting pattern for tool-using agents
- MCP Tools: Native support for Model Context Protocol
- Context Management: Maintain conversation context across interactions
- Async Support: Built for async/await patterns

## 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

| Tool slug | Name | Description |
|---|---|---|
| `PRISMA_CREATE_CONNECTION` | Create Database Connection | Create new API key connection for database access. Creates connection string with embedded credentials for application database access. Returns complete connection details ready for immediate use. |
| `PRISMA_CREATE_DATABASE` | Create Project Database | Create new postgres database in an existing Prisma project. Creates database in specified region with connection strings and API keys. Returns complete database details ready for immediate use. |
| `PRISMA_CREATE_PROJECT` | Create Prisma Project | Create new Prisma project with managed postgres database. Creates project in authenticated user's workspace with postgres database in specified region. Returns complete project details including connection strings and API keys. |
| `PRISMA_DELETE_CONNECTION` | Delete Database Connection | Permanently delete database connection and revoke API key access. WARNING: This immediately revokes database access for any applications using this connection string. Ensure no critical systems depend on this connection. |
| `PRISMA_DELETE_DATABASE` | Delete Prisma Database | Permanently delete Prisma database and all stored data. WARNING: This action cannot be undone. All data in the database will be permanently destroyed. Default databases typically cannot be deleted. |
| `PRISMA_DELETE_PROJECT` | Delete Prisma Project | Permanently delete Prisma project and all associated resources. WARNING: This action cannot be undone. All databases, environments, and project data will be permanently destroyed. Use with extreme caution in production environments. |
| `PRISMA_EXECUTE_SQL_COMMAND` | Execute SQL Command | Execute SQL commands that modify database data or structure. Runs INSERT, UPDATE, DELETE, CREATE TABLE, and other data modification commands safely through PostgreSQL driver with parameterized query support. |
| `PRISMA_EXECUTE_SQL_QUERY` | Execute SQL Query | Execute SQL SELECT queries against Prisma Postgres databases. Runs read-only queries safely through direct PostgreSQL connection with SSL. Uses credentials from create_connection action (host, user, pass fields). Perfect for data analysis, schema inspection, and reporting operations. |
| `PRISMA_GET_DATABASE` | Get Prisma Database | Retrieve specific Prisma database by ID. Returns database details including status, project context, and regional deployment. Use for database monitoring, validation, and administrative operations. |
| `PRISMA_GET_DATABASE_USAGE` | Get Database Usage Metrics | Retrieve usage metrics for a specific Prisma database. Returns metrics including storage usage and operation counts (reads/writes) for the specified time period. Use for monitoring resource consumption, cost analysis, and capacity planning. |
| `PRISMA_GET_PROJECT` | Get Prisma Project | Retrieve specific Prisma project by ID. Returns project details including name, creation timestamp, and workspace information. Use for project detail views, validation, and administrative operations. |
| `PRISMA_INSPECT_DATABASE_SCHEMA` | Inspect Database Schema | Inspect database schema structure and table information. Returns comprehensive schema details including tables, columns, data types, constraints, and relationships. Essential for understanding database structure before executing queries. |
| `PRISMA_LIST_ACCELERATE_REGIONS` | List Prisma Accelerate Regions | Retrieve all available regions for Prisma Accelerate. Returns regions where Accelerate global database cache can be deployed. Use for cache region selection to minimize latency for your users. |
| `PRISMA_LIST_BACKUPS` | List Database Backups | Retrieve list of available backups for a specific database. Returns backup details including status, size, type, and restoration readiness. Use for backup monitoring, restoration planning, and compliance auditing. |
| `PRISMA_LIST_CONNECTIONS` | List Database Connections | Retrieve paginated list of connections for a specific database. Returns connection details including names, creation dates, and database context. Use for API key management, security audits, and access control. |
| `PRISMA_LIST_DATABASES` | List Project Databases | Retrieve paginated list of databases for a specific Prisma project. Returns database details including status, region, and project context. Use for database discovery, monitoring, and project administration. |
| `PRISMA_LIST_POSTGRES_REGIONS` | List Prisma Postgres Regions | Retrieve all available regions for Prisma Postgres. Returns regions where Prisma Postgres databases can be deployed with current availability status. Use for region selection during database creation and capacity planning. |
| `PRISMA_LIST_PROJECTS` | List Prisma Projects | Retrieve paginated list of Prisma projects accessible to authenticated user. Returns project IDs, names, workspace info, and timestamps with cursor-based pagination. Use for project discovery, UI selection flows, and administrative operations. |
| `PRISMA_LIST_WORKSPACE_INTEGRATIONS` | List Workspace Integrations | Retrieve paginated list of integrations for a specific Prisma workspace. Returns integration details including OAuth client info, granted scopes, and creator. Use for security audits, integration management, and workspace administration. |
| `PRISMA_LIST_WORKSPACES` | List Prisma Workspaces | Retrieve paginated list of Prisma workspaces accessible to authenticated user. Returns workspace IDs, names, creation timestamps with cursor-based pagination. Use for workspace discovery, UI selection flows, and administrative operations. |
| `PRISMA_RESTORE_BACKUP` | Restore Database Backup | Restore database backup to new database instance. Creates new database from existing backup with specified name. Operation is asynchronous - monitor the returned database status for completion. Restoration may take several minutes. |
| `PRISMA_TRANSFER_PROJECT` | Transfer Prisma Project | Transfer Prisma project ownership to another user's workspace. Transfers project ownership from the current authenticated user to the recipient specified by their OAuth2 access token. This is typically used in partner integrations where databases are provisioned on the partner's workspace and later transferred to end users. The project and all its databases are moved to the recipient's workspace. The current owner loses access unless the new owner explicitly grants it. Requirements: - Valid project ID owned by the current user - Valid OAuth2 access token for the recipient user - Recipient workspace must have sufficient quota for the project |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Prisma MCP server is an implementation of the Model Context Protocol that connects your AI agent to Prisma. It provides structured and secure access so your agent can perform Prisma operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

Before you begin, make sure you have:
- Python 3.8/Node 16 or higher installed
- A Composio account with the API key
- An OpenAI API key
- A Prisma account and project
- Basic familiarity with async Python/Typescript

### 1. Getting API Keys for OpenAI, Composio, and Prisma

No description provided.

### 2. Installing dependencies

No description provided.
```python
pip install composio-llamaindex llama-index llama-index-llms-openai llama-index-tools-mcp python-dotenv
```

```typescript
npm install @composio/llamaindex @llamaindex/openai @llamaindex/tools @llamaindex/workflow dotenv
```

### 3. Set environment variables

Create a .env file in your project root:
These credentials will be used to:
- Authenticate with OpenAI's GPT-5 model
- Connect to Composio's Tool Router
- Identify your Composio user session for Prisma access
```bash
OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id
```

### 4. Import modules

No description provided.
```python
import asyncio
import os
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()
```

```typescript
import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();
```

### 5. Load environment variables and initialize Composio

No description provided.
```python
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set in the environment")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment")
```

```typescript
const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!COMPOSIO_API_KEY) throw new Error("COMPOSIO_API_KEY is not set");
if (!COMPOSIO_USER_ID) throw new Error("COMPOSIO_USER_ID is not set");
```

### 6. Create a Tool Router session and build the agent function

What's happening here:
- We create a Composio client using your API key and configure it with the LlamaIndex provider
- We then create a tool router MCP session for your user, specifying the toolkits we want to use (in this case, prisma)
- The session returns an MCP HTTP endpoint URL that acts as a gateway to all your configured tools
- LlamaIndex will connect to this endpoint to dynamically discover and use the available Prisma tools.
- The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.
```python
async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["prisma"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")

    description = "An agent that uses Composio Tool Router MCP tools to perform Prisma actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Prisma actions.
    """
    return ReActAgent(tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True)
```

```typescript
async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["prisma"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
        description : "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Prisma actions." ,
    llm,
    tools,
  });

  return agent;
}
```

### 7. Create an interactive chat loop

No description provided.
```python
async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")
```

```typescript
async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}
```

### 8. Define the main entry point

What's happening here:
- We're orchestrating the entire application flow
- The agent gets built with proper error handling
- Then we kick off the interactive chat loop so you can start talking to Prisma
```python
async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")
```

```typescript
async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err) {
    console.error("Failed to start agent:", err);
    process.exit(1);
  }
}

main();
```

### 9. Run the agent

When prompted, authenticate and authorise your agent with Prisma, then start asking questions.
```bash
python llamaindex_agent.py
```

```typescript
npx ts-node llamaindex-agent.ts
```

## Complete Code

```python
import asyncio
import os
import signal
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["prisma"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")
    description = "An agent that uses Composio Tool Router MCP tools to perform Prisma actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Prisma actions.
    """
    return ReActAgent(
        tools=tools,
        llm=llm,
        description=description,
        system_prompt=system_prompt,
        verbose=True,
    );

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")
```

```typescript
import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";
import { LlamaindexProvider } from "@composio/llamaindex";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();

const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) {
    throw new Error("OPENAI_API_KEY is not set in the environment");
  }
if (!COMPOSIO_API_KEY) {
    throw new Error("COMPOSIO_API_KEY is not set in the environment");
  }
if (!COMPOSIO_USER_ID) {
    throw new Error("COMPOSIO_USER_ID is not set in the environment");
  }

async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["prisma"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
    description:
      "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Prisma actions." ,
    llm,
    tools,
  });

  return agent;
}

async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}

async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err: any) {
    console.error("Failed to start agent:", err?.message ?? err);
    process.exit(1);
  }
}

main();
```

## Conclusion

You've successfully connected Prisma to LlamaIndex through Composio's Tool Router MCP layer.
Key takeaways:
- Tool Router dynamically exposes Prisma tools through an MCP endpoint
- LlamaIndex's ReActAgent handles reasoning and orchestration; Composio handles integrations
- The agent becomes more capable without increasing prompt size
- Async Python provides clean, efficient execution of agent workflows
You can easily extend this to other toolkits like Gmail, Notion, Stripe, GitHub, and more by adding them to the toolkits parameter.

## How to build Prisma MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/prisma/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/prisma/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/prisma/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/prisma/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/prisma/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/prisma/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/prisma/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/prisma/framework/cli)
- [Google ADK](https://composio.dev/toolkits/prisma/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/prisma/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/prisma/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/prisma/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/prisma/framework/crew-ai)

## Related Toolkits

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- [Codeinterpreter](https://composio.dev/toolkits/codeinterpreter) - Codeinterpreter is a Python-based coding environment with built-in data analysis and visualization. It lets you instantly run scripts, plot results, and prototype solutions inside supported platforms.
- [GitHub](https://composio.dev/toolkits/github) - GitHub is a code hosting platform for version control and collaborative software development. It streamlines project management, code review, and team workflows in one place.
- [Ably](https://composio.dev/toolkits/ably) - Ably is a real-time messaging platform for live chat and data sync in modern apps. It offers global scale and rock-solid reliability for seamless, instant experiences.
- [Abuselpdb](https://composio.dev/toolkits/abuselpdb) - Abuselpdb is a central database for reporting and checking IPs linked to malicious online activity. Use it to quickly identify and report suspicious or abusive IP addresses.
- [Alchemy](https://composio.dev/toolkits/alchemy) - Alchemy is a blockchain development platform offering APIs and tools for Ethereum apps. It simplifies building and scaling Web3 projects with robust infrastructure.
- [Algolia](https://composio.dev/toolkits/algolia) - Algolia is a hosted search API that powers lightning-fast, relevant search experiences for web and mobile apps. It helps developers deliver instant, typo-tolerant, and scalable search without complex infrastructure.
- [Anchor browser](https://composio.dev/toolkits/anchor_browser) - Anchor browser is a developer platform for AI-powered web automation. It transforms complex browser actions into easy API endpoints for streamlined web interaction.
- [Apiflash](https://composio.dev/toolkits/apiflash) - Apiflash is a website screenshot API for programmatically capturing web pages. It delivers high-quality screenshots on demand for automation, monitoring, or reporting.
- [Apiverve](https://composio.dev/toolkits/apiverve) - Apiverve delivers a suite of powerful APIs that simplify integration for developers. It's designed for reliability and scalability so you can build faster, smarter applications without the integration headache.
- [Appcircle](https://composio.dev/toolkits/appcircle) - Appcircle is an enterprise-grade mobile CI/CD platform for building, testing, and publishing mobile apps. It streamlines mobile DevOps so teams ship faster and with more confidence.
- [Appdrag](https://composio.dev/toolkits/appdrag) - Appdrag is a cloud platform for building websites, APIs, and databases with drag-and-drop tools and code editing. It accelerates development and iteration by combining hosting, database management, and low-code features in one place.
- [Appveyor](https://composio.dev/toolkits/appveyor) - AppVeyor is a cloud-based continuous integration service for building, testing, and deploying applications. It helps developers automate and streamline their software delivery pipelines.
- [Backendless](https://composio.dev/toolkits/backendless) - Backendless is a backend-as-a-service platform for mobile and web apps, offering database, file storage, user authentication, and APIs. It helps developers ship scalable applications faster without managing server infrastructure.
- [Baserow](https://composio.dev/toolkits/baserow) - Baserow is an open-source no-code database platform for building collaborative data apps. It makes it easy for teams to organize data and automate workflows without writing code.
- [Bench](https://composio.dev/toolkits/bench) - Bench is a benchmarking tool for automated performance measurement and analysis. It helps you quickly evaluate, compare, and track your systems or workflows.
- [Better stack](https://composio.dev/toolkits/better_stack) - Better Stack is a monitoring, logging, and incident management solution for apps and services. It helps teams ensure application reliability and performance with real-time insights.
- [Bitbucket](https://composio.dev/toolkits/bitbucket) - Bitbucket is a Git-based code hosting and collaboration platform for teams. It enables secure repository management and streamlined code reviews.
- [Blazemeter](https://composio.dev/toolkits/blazemeter) - Blazemeter is a continuous testing platform for web and mobile app performance. It empowers teams to automate and analyze large-scale tests with ease.
- [Blocknative](https://composio.dev/toolkits/blocknative) - Blocknative delivers real-time mempool monitoring and transaction management for public blockchains. Instantly track pending transactions and optimize blockchain interactions with live data.

## Frequently Asked Questions

### 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 LlamaIndex?

Yes, you can. LlamaIndex 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.

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)