# How to integrate Platerecognizer MCP with Claude Agent SDK

```json
{
  "title": "How to integrate Platerecognizer MCP with Claude Agent SDK",
  "toolkit": "Platerecognizer",
  "toolkit_slug": "platerecognizer",
  "framework": "Claude Agent SDK",
  "framework_slug": "claude-agents-sdk",
  "url": "https://composio.dev/toolkits/platerecognizer/framework/claude-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/platerecognizer/framework/claude-agents-sdk.md",
  "updated_at": "2026-05-12T10:22:18.033Z"
}
```

## Introduction

This guide walks you through connecting Platerecognizer to the Claude Agent SDK using the Composio tool router. By the end, you'll have a working Platerecognizer agent that can show your alpr usage stats for june, how many plates did we scan this month?, get daily snapshot recognition call counts through natural language commands.
This guide will help you understand how to give your Claude Agent SDK agent real control over a Platerecognizer account through Composio's Platerecognizer MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Platerecognizer with

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

## TL;DR

Here's what you'll learn:
- Get and set up your Claude/Anthropic and Composio API keys
- Install the necessary dependencies
- Initialize Composio and create a Tool Router session for Platerecognizer
- Configure an AI agent that can use Platerecognizer as a tool
- Run a live chat session where you can ask the agent to perform Platerecognizer operations

## What is Claude Agent SDK?

The Claude Agent SDK is Anthropic's official framework for building AI agents powered by Claude. It provides a streamlined interface for creating agents with MCP tool support and conversation management.
Key features include:
- Native MCP Support: Built-in support for Model Context Protocol servers
- Permission Modes: Control tool execution permissions
- Streaming Responses: Real-time response streaming for interactive applications
- Context Manager: Clean async context management for sessions

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

The Platerecognizer MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Platerecognizer account. It provides structured and secure access to your license plate recognition data, so your agent can monitor usage, retrieve recognition statistics, track monthly activity, and help you stay on top of your ALPR operations.
- Monitor monthly recognition usage: Instantly check how many snapshot recognition calls you've made during the current month to manage your account limits.
- Retrieve up-to-date usage statistics: Ask your agent for real-time statistics on your Platerecognizer snapshot API activity to spot trends or anomalies.
- Automate usage tracking: Set up workflows where your agent periodically fetches and summarizes ALPR statistics for compliance or reporting.
- Stay informed on API consumption: Let your agent proactively notify you as you approach usage thresholds, helping you avoid interruptions.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `PLATERECOGNIZER_READ_LICENSE_PLATE` | Read License Plate | Tool to read license plates from images with confidence scores and optional vehicle details. Use when you need to extract license plate text, region information, or analyze vehicle attributes from images. |
| `PLATERECOGNIZER_SNAPSHOT_GET_STATISTICS` | Snapshot Get Statistics | Tool to retrieve usage statistics for the current month's Snapshot API recognition calls. Use after making Snapshot API calls to monitor monthly usage. |

## Supported Triggers

None listed.

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

The Platerecognizer MCP server is an implementation of the Model Context Protocol that connects your AI agent to Platerecognizer. It provides structured and secure access so your agent can perform Platerecognizer 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 starting, make sure you have:
- Composio API Key and Claude/Anthropic API Key
- Primary know-how of Claude Agents SDK
- A Platerecognizer account
- Some knowledge of Python

### 1. Getting API Keys for Claude/Anthropic and Composio

Claude/Anthropic API Key
- Go to the [Anthropic Console](https://console.anthropic.com/settings/organization/api-keys) and create an API key. You'll need credits to use the models.
- Keep the API key safe.
Composio API Key
- Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

No description provided.
```python
pip install composio-anthropic claude-agent-sdk python-dotenv
```

```typescript
npm install @anthropic-ai/claude-agent-sdk @composio/core dotenv
```

### 3. Set up environment variables

Create a .env file in your project root.
What's happening:
- COMPOSIO_API_KEY authenticates with Composio
- USER_ID identifies the user for session management
- ANTHROPIC_API_KEY authenticates with Anthropic/Claude
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
ANTHROPIC_API_KEY=your_anthropic_api_key_here
```

### 4. Import dependencies

No description provided.
```python
import asyncio
from claude_agent_sdk import ClaudeSDKClient, ClaudeAgentOptions
import os
from composio import Composio
from dotenv import load_dotenv

load_dotenv()
```

```typescript
import 'dotenv/config';
import readline from 'node:readline';
import { Composio } from '@composio/core';
import { query, type Options } from "@anthropic-ai/claude-agent-sdk";

dotenv.config();
```

### 5. Create a Composio instance and Tool Router session

No description provided.
```python
async def chat_with_remote_mcp():
    api_key = os.getenv("COMPOSIO_API_KEY")
    if not api_key:
        raise RuntimeError("COMPOSIO_API_KEY is not set")

    composio = Composio(api_key=api_key)

    # Create Tool Router session for Platerecognizer
    mcp_server = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["platerecognizer"]
    )

    url = mcp_server.mcp.url

    if not url:
        raise ValueError("Session URL not found")
```

```typescript
async function chat() {
  const { COMPOSIO_API_KEY, USER_ID } = process.env;
  if (!COMPOSIO_API_KEY || !USER_ID) {
    throw new Error('COMPOSIO_API_KEY and USER_ID required in .env');
  }

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

  // Create Tool Router session for Platerecognizer
  const session = await composio.create(USER_ID, {
    toolkits: ['platerecognizer'],
  });
  const mcpUrl = session?.mcp.url;
```

### 6. Configure Claude Agent with MCP

No description provided.
```python
# Configure remote MCP server for Claude
options = ClaudeAgentOptions(
    permission_mode="bypassPermissions",
    mcp_servers={
        "composio": {
            "type": "http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    },
    system_prompt="You are a helpful assistant with access to Platerecognizer tools via Composio.",
    max_turns=10
)
```

```typescript
const options: Options = {
  permissionMode: 'bypassPermissions',
  mcpServers: {
    composio: {
      type: 'http',
      url: mcpUrl,
      headers: { 'x-api-key': COMPOSIO_API_KEY }
    }
  },
  systemPrompt: 'You are a helpful assistant with access to Platerecognizer tools via Composio.',
  maxTurns: 10,
};
```

### 7. Create client and start chat loop

No description provided.
```python
# Create client with context manager
async with ClaudeSDKClient(options=options) as client:
    print("\nChat started. Type 'exit' or 'quit' to end.\n")

    # Main chat loop
    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit"}:
            print("Goodbye!")
            break

        # Send query
        await client.query(user_input)

        # Receive and print response
        print("Claude: ", end="", flush=True)
        async for message in client.receive_response():
            if hasattr(message, "content"):
                for block in message.content:
                    if hasattr(block, "text"):
                        print(block.text, end="", flush=True)
        print()
```

```typescript
const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
  });

  console.log('\nChat started. Type "exit" to quit.\n');

  let isProcessing = false;

  async function ask(prompt: string) {
    isProcessing = true;
    rl.pause();

    process.stdout.write('Claude is thinking...');
    const stream = query({ prompt, options });

    let firstChunk = true;
    for await (const msg of stream) {
      const content = (msg as any).message?.content || (msg as any).content;
      if (Array.isArray(content)) {
        for (const block of content) {
          if (block.type === 'text' && block.text) {
            if (firstChunk) {
              process.stdout.write('\r\x1b[K');
              process.stdout.write('Claude: ');
              firstChunk = false;
            }
            process.stdout.write(block.text);
          }
        }
      }
    }
    process.stdout.write('\n\n');

    isProcessing = false;
    rl.resume();
    rl.prompt();
  }

  rl.on('line', async (line) => {
    if (isProcessing) return;

    const input = line.trim();
    if (input === 'exit') {
      rl.close();
      process.exit(0);
    }
    if (input) await ask(input);
    else rl.prompt();
  });

  await ask('What can you help me with?');
}
```

### 8. Run the application

No description provided.
```python
if __name__ == "__main__":
    asyncio.run(chat_with_remote_mcp())
```

```typescript
try {
  await chat();
} catch (error) {
  console.error(error);
  process.exit(1);
}
```

## Complete Code

```python
import asyncio
from claude_agent_sdk import ClaudeSDKClient, ClaudeAgentOptions
import os
from composio import Composio
from dotenv import load_dotenv

load_dotenv()

async def chat_with_remote_mcp():
    api_key = os.getenv("COMPOSIO_API_KEY")
    if not api_key:
        raise RuntimeError("COMPOSIO_API_KEY is not set")

    composio = Composio(api_key=api_key)

    # Create Tool Router session for Platerecognizer
    mcp_server = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["platerecognizer"]
    )

    url = mcp_server.mcp.url

    if not url:
        raise ValueError("Session URL not found")

    # Configure remote MCP server for Claude
    options = ClaudeAgentOptions(
        permission_mode="bypassPermissions",
        mcp_servers={
            "composio": {
                "type": "http",
                "url": url,
                "headers": {
                    "x-api-key": os.getenv("COMPOSIO_API_KEY")
                }
            }
        },
        system_prompt="You are a helpful assistant with access to Platerecognizer tools via Composio.",
        max_turns=10
    )

    # Create client with context manager
    async with ClaudeSDKClient(options=options) as client:
        print("\nChat started. Type 'exit' or 'quit' to end.\n")

        # Main chat loop
        while True:
            user_input = input("You: ").strip()
            if user_input.lower() in {"exit", "quit"}:
                print("Goodbye!")
                break

            # Send query
            await client.query(user_input)

            # Receive and print response
            print("Claude: ", end="", flush=True)
            async for message in client.receive_response():
                if hasattr(message, "content"):
                    for block in message.content:
                        if hasattr(block, "text"):
                            print(block.text, end="", flush=True)
            print()

if __name__ == "__main__":
    asyncio.run(chat_with_remote_mcp())
```

```typescript
import 'dotenv/config';
import readline from 'node:readline';
import { Composio } from '@composio/core';
import { query, type Options } from "@anthropic-ai/claude-agent-sdk";

async function chat() {
  const { COMPOSIO_API_KEY, USER_ID } = process.env;
  if (!COMPOSIO_API_KEY || !USER_ID) {
    throw new Error('COMPOSIO_API_KEY and USER_ID required in .env');
  }

  const composio = new Composio({ apiKey: COMPOSIO_API_KEY });
  const session = await composio.create(USER_ID, {
    toolkits: ['platerecognizer']
  });
  const mcp_url = session?.mcp.url;

  const options: Options = {
    permissionMode: 'bypassPermissions',
    mcpServers: {
      composio: {
        type: 'http',
        url: mcp_url,
        headers: { 'x-api-key': COMPOSIO_API_KEY }
      }
    },
    systemPrompt: 'You are a helpful assistant with access to Platerecognizer tools via Composio.',
    maxTurns: 10,
  };

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
  });

  console.log('\nChat started. Type "exit" to quit.\n');

  let isProcessing = false;

  async function ask(prompt: string) {
    isProcessing = true;
    rl.pause();

    process.stdout.write('Claude is thinking...');
    const stream = query({ prompt, options });

    let firstChunk = true;
    for await (const msg of stream) {
      const content = (msg as any).message?.content || (msg as any).content;
      if (Array.isArray(content)) {
        for (const block of content) {
          if (block.type === 'text' && block.text) {
            if (firstChunk) {
              process.stdout.write('\r\x1b[K');
              process.stdout.write('Claude: ');
              firstChunk = false;
            }
            process.stdout.write(block.text);
          }
        }
      }
    }
    process.stdout.write('\n\n');

    isProcessing = false;
    rl.resume();
    rl.prompt();
  }

  rl.on('line', async (line) => {
    if (isProcessing) return;

    const input = line.trim();
    if (input === 'exit') {
      rl.close();
      process.exit(0);
    }
    if (input) await ask(input);
    else rl.prompt();
  });

  await ask('What can you help me with?');
}

try {
  await chat();
} catch (error) {
  console.error(error);
  process.exit(1);
}
```

## Conclusion

You've successfully built a Claude Agent SDK agent that can interact with Platerecognizer through Composio's Tool Router.
Key features:
- Native MCP support through Claude's agent framework
- Streaming responses for real-time interaction
- Permission bypass for smooth automated workflows
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

## How to build Platerecognizer MCP Agent with another framework

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

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- [Api sports](https://composio.dev/toolkits/api_sports) - Api sports is a comprehensive sports data platform covering 2,000+ competitions with live scores and 15+ years of stats. Instantly access up-to-date sports information for analysis, apps, or chatbots.
- [Apify](https://composio.dev/toolkits/apify) - Apify is a cloud platform for building, deploying, and managing web scraping and automation tools called Actors. It lets you automate data extraction and workflow tasks at scale—no infrastructure headaches.
- [Autom](https://composio.dev/toolkits/autom) - Autom is a lightning-fast search engine results data platform for Google, Bing, and Brave. Developers use it to access fresh, low-latency SERP data on demand.
- [Beaconchain](https://composio.dev/toolkits/beaconchain) - Beaconchain is a real-time analytics platform for Ethereum 2.0's Beacon Chain. It provides detailed insights into validators, blocks, and overall network performance.
- [Big data cloud](https://composio.dev/toolkits/big_data_cloud) - BigDataCloud provides APIs for geolocation, reverse geocoding, and address validation. Instantly access reliable location intelligence to enhance your applications and workflows.
- [Bigpicture io](https://composio.dev/toolkits/bigpicture_io) - BigPicture.io offers APIs for accessing detailed company and profile data. Instantly enrich your applications with up-to-date insights on 20M+ businesses.
- [Bitquery](https://composio.dev/toolkits/bitquery) - Bitquery is a blockchain data platform offering indexed, real-time, and historical data from 40+ blockchains via GraphQL APIs. Get unified, reliable access to complex on-chain data for analytics, trading, and research.
- [Brightdata](https://composio.dev/toolkits/brightdata) - Brightdata is a leading web data platform offering advanced scraping, SERP APIs, and anti-bot tools. It lets you collect public web data at scale, bypassing blocks and friction.
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- [Byteforms](https://composio.dev/toolkits/byteforms) - Byteforms is an all-in-one platform for creating forms, managing submissions, and integrating data. It streamlines workflows by centralizing form data collection and automation.
- [Cabinpanda](https://composio.dev/toolkits/cabinpanda) - Cabinpanda is a data collection platform for building and managing online forms. It helps streamline how you gather, organize, and analyze responses.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Platerecognizer MCP?

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

### Can I use Tool Router MCP with Claude Agent SDK?

Yes, you can. Claude Agent SDK 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 Platerecognizer tools.

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

Yes, absolutely. You can configure which Platerecognizer 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 Platerecognizer data and credentials are handled as safely as possible.

---
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