# How to integrate Placekey MCP with LangChain

```json
{
  "title": "How to integrate Placekey MCP with LangChain",
  "toolkit": "Placekey",
  "toolkit_slug": "placekey",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/placekey/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/placekey/framework/langchain.md",
  "updated_at": "2026-05-12T10:22:09.314Z"
}
```

## Introduction

This guide walks you through connecting Placekey to LangChain using the Composio tool router. By the end, you'll have a working Placekey agent that can find placekey for this street address, get latitude and longitude from an address, convert gps coordinates to a placekey through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Placekey account through Composio's Placekey MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Placekey with

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

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Connect your Placekey project to Composio
- Create a Tool Router MCP session for Placekey
- Initialize an MCP client and retrieve Placekey tools
- Build a LangChain agent that can interact with Placekey
- Set up an interactive chat interface for testing

## What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.
Key features include:
- Agent Framework: Build agents that can use tools and make decisions
- MCP Integration: Connect to external services through Model Context Protocol adapters
- Memory Management: Maintain conversation history across interactions
- Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

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

The Placekey MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Placekey account. It provides structured and secure access to location standardization tools, so your agent can perform actions like converting addresses to Placekeys, retrieving geocodes, and mapping locations on your behalf.
- Address to Placekey conversion: Instantly convert any physical address into a unique Placekey identifier for seamless data matching and enrichment.
- Geocode retrieval from address: Have your agent fetch latitude, longitude, and full geocode details for any address, complete with Placekey and location info.
- Placekey generation from coordinates: Quickly generate a Placekey for any geographic coordinates, making it easy to standardize and deduplicate location data.
- Location deduplication and validation: Let your agent use Placekeys to match, validate, and deduplicate different representations of the same physical place across your datasets.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `PLACEKEY_GET_GEOCODE_FROM_ADDRESS` | Get Geocode From Address | This tool retrieves geocode information (latitude and longitude) for a given address using the Placekey API. It accepts address components (street_address, city, region, postal_code, iso_country_code) and returns geocode data including the unique Placekey identifier and location details. |
| `PLACEKEY_GET_PLACEKEY` | Get Placekey | Tool to get a Placekey for a single location using address, coordinates, or POI details. Use when you need to obtain a unique identifier for a physical place with support for address fields, coordinates, location name, and optional metadata for enhanced matching. |
| `PLACEKEY_GET_PLACEKEY_FROM_ADDRESS` | Get placekey from address | Convert a physical address into a unique Placekey identifier. The Placekey is a universal standard identifier for any physical place that helps in location matching, enrichment, and deduplication. |
| `PLACEKEY_GET_PLACEKEYS_BULK` | Get Placekeys Bulk | Get Placekeys for multiple locations in bulk (up to 100 queries per request). All queries must have the same iso_country_code. Supports address, coordinates, and POI queries with optional query_id for tracking. Returns an array of Placekey results for each query. |

## Supported Triggers

None listed.

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

The Placekey MCP server is an implementation of the Model Context Protocol that connects your AI agent to Placekey. It provides structured and secure access so your agent can perform Placekey 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

No description provided.

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

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](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-langchain langchain-mcp-adapters langchain python-dotenv
```

```typescript
npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv
```

### 3. Set up environment variables

Create a .env file in your project root.
What's happening:
- COMPOSIO_API_KEY authenticates your requests to Composio's API
- COMPOSIO_USER_ID identifies the user for session management
- OPENAI_API_KEY enables access to OpenAI's language models
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here
```

### 4. Import dependencies

No description provided.
```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
```

```typescript
import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();
```

### 5. Initialize Composio client

What's happening:
- We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
- Creating a Composio instance that will manage our connection to Placekey tools
- Validating that COMPOSIO_USER_ID is also set before proceeding
```python
async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
```

```typescript
const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });
```

### 6. Create a Tool Router session

What's happening:
- We're creating a Tool Router session that gives your agent access to Placekey tools
- The create method takes the user ID and specifies which toolkits should be available
- The returned session.mcp.url is the MCP server URL that your agent will use
- This approach allows the agent to dynamically load and use Placekey tools as needed
```python
# Create Tool Router session for Placekey
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['placekey']
)

url = session.mcp.url
```

```typescript
const session = await composio.create(
    userId as string,
    {
        toolkits: ['placekey']
    }
);

const url = session.mcp.url;
```

### 7. Configure the agent with the MCP URL

No description provided.
```python
client = MultiServerMCPClient({
    "placekey-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
```

```typescript
const client = new MultiServerMCPClient({
    "placekey-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });
```

### 8. Set up interactive chat interface

No description provided.
```python
conversation_history = []

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

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

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

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
```

```typescript
let conversationHistory: any[] = [];

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

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

rl.prompt();

rl.on('line', async (userInput: string) => {
    const trimmedInput = userInput.trim();

    if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
        console.log("\nGoodbye!");
        rl.close();
        process.exit(0);
    }

    if (!trimmedInput) {
        rl.prompt();
        return;
    }

    conversationHistory.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\n👋 Session ended.');
        process.exit(0);
    });
```

### 9. Run the application

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

```typescript
main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
```

## Complete Code

```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['placekey']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "placekey-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Placekey related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

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

```typescript
import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['placekey']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "placekey-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Placekey related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    rl.prompt();

    rl.on('line', async (userInput: string) => {
        const trimmedInput = userInput.trim();
        
        if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
            console.log("\nGoodbye!");
            rl.close();
            process.exit(0);
        }
        
        if (!trimmedInput) {
            rl.prompt();
            return;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\nSession ended.');
        process.exit(0);
    });
}

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
```

## Conclusion

You've successfully built a LangChain agent that can interact with Placekey through Composio's Tool Router.
Key features of this implementation:
- Dynamic tool loading through Composio's Tool Router
- Conversation history maintenance for context-aware responses
- Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

## How to build Placekey MCP Agent with another framework

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

## Related Toolkits

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- [ClickHouse](https://composio.dev/toolkits/clickhouse) - ClickHouse is an open-source, column-oriented database for real-time analytics and big data processing using SQL. Its lightning-fast query performance makes it ideal for handling large datasets and delivering instant insights.
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- [Control d](https://composio.dev/toolkits/control_d) - Control d is a customizable DNS filtering and traffic redirection platform. It helps you manage internet access, enforce policies, and monitor usage across devices and networks.
- [Databox](https://composio.dev/toolkits/databox) - Databox is a business analytics platform that connects your data from any tool and device. It helps you track KPIs, build dashboards, and discover actionable insights.
- [Databricks](https://composio.dev/toolkits/databricks) - Databricks is a unified analytics platform for big data and AI on the lakehouse architecture. It empowers data teams to collaborate, analyze, and build scalable solutions efficiently.
- [Datagma](https://composio.dev/toolkits/datagma) - Datagma delivers data intelligence and analytics for business growth and market discovery. Get actionable market insights and track competitors to inform your strategy.
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- [Elasticsearch](https://composio.dev/toolkits/elasticsearch) - Elasticsearch is a distributed, RESTful search and analytics engine for all types of data. It delivers fast, scalable search and powerful analytics across massive datasets.

## Frequently Asked Questions

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

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

### Can I use Tool Router MCP with LangChain?

Yes, you can. LangChain 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 Placekey tools.

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

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

---
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