# How to integrate Apiverve MCP with LangChain

```json
{
  "title": "How to integrate Apiverve MCP with LangChain",
  "toolkit": "Apiverve",
  "toolkit_slug": "apiverve",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/apiverve/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/apiverve/framework/langchain.md",
  "updated_at": "2026-05-12T10:01:41.368Z"
}
```

## Introduction

This guide walks you through connecting Apiverve to LangChain using the Composio tool router. By the end, you'll have a working Apiverve agent that can convert 100 usd to japanese yen, get air quality details for paris, find antonyms for the word 'happy' through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Apiverve account through Composio's Apiverve MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Apiverve with

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

## TL;DR

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

The Apiverve MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Apiverve account. It provides structured and secure access to a broad suite of APIs, so your agent can perform actions like fetching real-time air quality, converting currencies, retrieving app data, calculating ages, and delivering word definitions or antonyms on your behalf.
- Real-time air quality reporting: Instantly get air quality data, including AQI, pollutant levels, and health recommendations for any city.
- Currency conversion automation: Effortlessly convert between currencies using up-to-date exchange rates, perfect for financial tasks and travel planning.
- App Store metadata retrieval: Fetch detailed information about apps from the app store, including ratings and descriptions, by supplying app IDs and country codes.
- Word definitions and antonyms: Ask your agent to define any word or find its opposites, supporting smarter text analysis and content creation.
- Travel and information utilities: Calculate age from a date of birth, get the distance between airports, or retrieve detailed airline and airport info—all with a simple prompt.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `APIVERVE_ADVICE_GENERATOR` | Advice Generator | Tool to generate a random piece of advice. Use when you need spontaneous guidance or motivation. |
| `APIVERVE_AGE_CALCULATOR` | Age Calculator | Tool to calculate age from date of birth. Use when you need a breakdown of years, months, weeks, and days from a given DOB. Example: "Calculate age for dob=1990-01-01" |
| `APIVERVE_AIRLINE_LOOKUP_NAME` | Get Airline Info by Name | Look up airline information by name. Returns airline details including IATA code (2-letter), ICAO code (3-letter), radio callsign, and country of operation. Supports partial name matching, so searching 'American' returns all airlines containing 'American' in their name. |
| `APIVERVE_AIRPORT_DISTANCE_IATA` | Get airport distance by IATA | Tool to get distance between two airports by their IATA codes. Use when you have valid airport IATA codes and need the flight distance. |
| `APIVERVE_AIRPORTS_LOOKUP_ICAO` | Get Airport Info by ICAO Code | Tool to get airport information by ICAO code. Use when you have a valid 4-letter ICAO code and need detailed airport information. |
| `APIVERVE_AIR_QUALITY` | Air Quality | Tool to get air quality data for a city. Use when you need current AQI, pollutant levels, and a health recommendation. |
| `APIVERVE_ANTONYM_FINDER` | Find antonyms for a word | Tool to get antonyms for a word. Use when you need opposite terms for text analysis. |
| `APIVERVE_APP_STORE_SCRAPER` | App Store Scraper | Fetch detailed metadata for an iOS/macOS app from the Apple App Store. Use this tool to retrieve comprehensive app information including title, description, ratings, reviews, pricing, screenshots, developer info, and version history. Common use cases: - Research competitor apps - Monitor app ratings and reviews - Get app details for app store optimization (ASO) - Verify app availability in specific countries Example: To get info for Candy Crush Saga in the US store, use appid='553834731' and country='us'. |
| `APIVERVE_CURRENCY_CONVERTER` | Currency Converter | Tool to convert currency rates. Use when you need to convert an amount between two currencies with the latest exchange rate. |
| `APIVERVE_DICTIONARY` | Get Word Definition | Tool to get the definition of a word. Use when you need to find the meaning of a specific word. E.g., "Define the word apple." |
| `APIVERVE_WEATHER_BY_CITY` | Weather by City | Tool to get current weather by city. Use when you need to obtain up-to-date weather details for a specific city after confirming the city name. Example: "What's the weather in Berlin?" |

## Supported Triggers

None listed.

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

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

url = session.mcp.url
```

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

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

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

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

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

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

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

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- [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.
- [Bolt iot](https://composio.dev/toolkits/bolt_iot) - Bolt IoT is a platform for building and managing IoT projects with cloud-based device control and monitoring. It makes connecting sensors and actuators to the internet seamless for automation and data insights.

## Frequently Asked Questions

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

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

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

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

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