# How to integrate Dropcontact MCP with LangChain

```json
{
  "title": "How to integrate Dropcontact MCP with LangChain",
  "toolkit": "Dropcontact",
  "toolkit_slug": "dropcontact",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/dropcontact/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/dropcontact/framework/langchain.md",
  "updated_at": "2026-05-12T10:09:57.161Z"
}
```

## Introduction

This guide walks you through connecting Dropcontact to LangChain using the Composio tool router. By the end, you'll have a working Dropcontact agent that can enrich a list of linkedin contacts, validate work emails for your leads, retrieve enrichment results for last upload through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Dropcontact account through Composio's Dropcontact MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Dropcontact with

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

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Connect your Dropcontact project to Composio
- Create a Tool Router MCP session for Dropcontact
- Initialize an MCP client and retrieve Dropcontact tools
- Build a LangChain agent that can interact with Dropcontact
- 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 Dropcontact MCP server, and what's possible with it?

The Dropcontact MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Dropcontact account. It provides structured and secure access to contact enrichment and B2B email finding, so your agent can perform actions like verifying professional email addresses, enriching contact lists, tracking enrichment status, and managing webhook subscriptions on your behalf.
- Batch contact enrichment: Instantly enrich up to 250 contacts at once with validated email addresses and company details, letting your agent automate lead research and CRM updates.
- Email verification and validation: Ensure the emails in your contact lists are professional and verified, reducing bounce rates and improving outreach quality.
- Retrieve enrichment results: Have your agent fetch completed enrichment data for submitted requests, so you can quickly access up-to-date contact intelligence.
- Manage webhook subscriptions: List and inspect your webhook subscriptions, making it easy to keep track of automated updates and integrations with your workflow.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `DROPCONTACT_CREATE_WEBHOOK_SUBSCRIPTION` | Create Webhook Subscription | Tool to create a new webhook subscription for receiving automatic notifications when enrichment results are ready. Use this instead of polling GET /v1/enrich/all to receive push notifications when contact enrichment processing completes. Currently only supports 'enrich_api_result' event type. |
| `DROPCONTACT_DELETE_WEBHOOK_SUBSCRIPTION` | Delete Webhook Subscription | Tool to delete a webhook subscription. Use when you need to remove a configured webhook and stop receiving notifications. Alternatively, you can pause a subscription by setting it to inactive using the update endpoint. |
| `DROPCONTACT_ENRICH_CONTACTS` | Initiate Contact Enrichment | Initiates asynchronous batch enrichment for up to 250 contacts with email finding, validation, and company information. Returns a request_id that must be used with the 'Retrieve Enrichment Results' action to fetch the enriched data. Each contact needs at least one of: email, OR (first_name + last_name + company), OR (full_name + company), OR LinkedIn URL. The enrichment typically completes within 30-60 seconds depending on batch size. |
| `DROPCONTACT_LIST_WEBHOOK_SUBSCRIPTIONS` | List Webhook Subscriptions | Tool to list webhook subscriptions. Use when you need to inspect your configured webhooks. |
| `DROPCONTACT_LIST_WEBHOOK_SUBSCRIPTIONS_V2` | List Webhook Subscriptions V2 | Tool to list all webhook subscriptions configured for the account. Returns webhook URLs, event types, and subscription details. Use when you need to inspect your configured webhooks. |
| `DROPCONTACT_RETRIEVE_ENRICHMENT_RESULTS` | Retrieve Enrichment Results | Retrieves enriched contact data by request ID after submitting contacts for enrichment. Use this tool to fetch the results of a contact enrichment request created with the 'Batch Enrich Contacts' action. The enrichment process may take 30-60 seconds. If the request is still processing, the response will indicate 'success=false' with a reason message. Once complete, you'll receive enriched data including emails with qualification status, LinkedIn profiles, company information, phone numbers, and location details. Note: You can retrieve partial results even if all contacts haven't been processed yet. |
| `DROPCONTACT_UPDATE_WEBHOOK_SUBSCRIPTION` | Update Webhook Subscription | Tool to update an existing webhook subscription. Use when you need to modify the callback URL, rate limiting settings, or active status. The event_type field cannot be changed after creation. |

## Supported Triggers

None listed.

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

The Dropcontact MCP server is an implementation of the Model Context Protocol that connects your AI agent to Dropcontact. It provides structured and secure access so your agent can perform Dropcontact 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 Dropcontact 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 Dropcontact 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 Dropcontact tools as needed
```python
# Create Tool Router session for Dropcontact
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['dropcontact']
)

url = session.mcp.url
```

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

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

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

No description provided.
```python
client = MultiServerMCPClient({
    "dropcontact-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({
    "dropcontact-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 Dropcontact 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 Dropcontact 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=['dropcontact']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "dropcontact-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 Dropcontact 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: ['dropcontact']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "dropcontact-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 Dropcontact 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 Dropcontact 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 Dropcontact MCP Agent with another framework

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

## Related Toolkits

- [Hubspot](https://composio.dev/toolkits/hubspot) - HubSpot is an all-in-one marketing, sales, and customer service platform. It lets teams nurture leads, automate outreach, and track every customer interaction in one place.
- [Pipedrive](https://composio.dev/toolkits/pipedrive) - Pipedrive is a sales management platform offering pipeline visualization, lead tracking, and workflow automation. It helps sales teams keep deals moving forward efficiently and never miss a follow-up.
- [Salesforce](https://composio.dev/toolkits/salesforce) - Salesforce is a leading CRM platform that helps businesses manage sales, service, and marketing. It centralizes customer data, enabling teams to drive growth and build strong relationships.
- [Apollo](https://composio.dev/toolkits/apollo) - Apollo is a CRM and lead generation platform that helps businesses discover contacts and manage sales pipelines. Use it to streamline customer outreach and track your deals from one place.
- [Attio](https://composio.dev/toolkits/attio) - Attio is a customizable CRM and workspace for managing your team's relationships and workflows. It helps teams organize contacts, automate tasks, and collaborate more efficiently.
- [Acculynx](https://composio.dev/toolkits/acculynx) - AccuLynx is a cloud-based roofing business management software for contractors. It streamlines project tracking, lead management, and document sharing.
- [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time.
- [Affinity](https://composio.dev/toolkits/affinity) - Affinity is a relationship intelligence CRM that helps private capital investors find, manage, and close more deals. It streamlines deal flow and surfaces key connections to help you win opportunities.
- [Agencyzoom](https://composio.dev/toolkits/agencyzoom) - AgencyZoom is a sales and performance platform built for P&C insurance agencies. It helps agents boost sales, retain clients, and analyze producer results in one place.
- [Bettercontact](https://composio.dev/toolkits/bettercontact) - Bettercontact is a smart contact enrichment tool for finding emails and phone numbers. It helps boost lead generation with automated, waterfall search across multiple sources.
- [Blackbaud](https://composio.dev/toolkits/blackbaud) - Blackbaud provides cloud-based software for nonprofits, schools, and healthcare institutions. It streamlines fundraising, donor management, and mission-driven operations.
- [Brilliant directories](https://composio.dev/toolkits/brilliant_directories) - Brilliant Directories is an all-in-one platform for building and managing online membership communities and business directories. It streamlines listings, member management, and engagement tools into a single, easy interface.
- [Capsule crm](https://composio.dev/toolkits/capsule_crm) - Capsule CRM is a user-friendly CRM platform for managing contacts and sales pipelines. It helps businesses organize relationships and streamline their sales process efficiently.
- [Centralstationcrm](https://composio.dev/toolkits/centralstationcrm) - CentralStationCRM is an easy-to-use CRM software focused on collaboration and long-term customer relationships. It helps teams manage contacts, deals, and communications all in one place.
- [Clientary](https://composio.dev/toolkits/clientary) - Clientary is a platform for managing clients, invoices, projects, proposals, and more. It streamlines client work and saves you serious admin time.
- [Close](https://composio.dev/toolkits/close) - Close is a CRM platform built for sales teams, combining calling, email automation, and predictive dialers. It streamlines sales workflows and boosts productivity with all-in-one communication tools.
- [Dynamics365](https://composio.dev/toolkits/dynamics365) - Dynamics 365 is Microsoft's platform combining CRM, ERP, and productivity apps. It streamlines sales, marketing, service, and operations in one place.
- [Espocrm](https://composio.dev/toolkits/espocrm) - EspoCRM is an open-source web application for managing customer relationships. It helps businesses organize contacts, track leads, and streamline their sales process.
- [Fireberry](https://composio.dev/toolkits/fireberry) - Fireberry is a CRM platform that streamlines customer and sales management. It helps businesses organize contacts, automate sales, and integrate with other business tools.
- [Firmao](https://composio.dev/toolkits/firmao) - Firmao is a business information platform offering company, industry, and market data. Use it to quickly research firms and gain competitive market insights.

## Frequently Asked Questions

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

With a standalone Dropcontact MCP server, the agents and LLMs can only access a fixed set of Dropcontact tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Dropcontact 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 Dropcontact tools.

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

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

---
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