# How to integrate Coinranking MCP with LangChain

```json
{
  "title": "How to integrate Coinranking MCP with LangChain",
  "toolkit": "Coinranking",
  "toolkit_slug": "coinranking",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/coinranking/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/coinranking/framework/langchain.md",
  "updated_at": "2026-05-06T08:06:54.912Z"
}
```

## Introduction

This guide walks you through connecting Coinranking to LangChain using the Composio tool router. By the end, you'll have a working Coinranking agent that can show top trending cryptocurrencies today, get bitcoin price history for last month, list coins with market cap over $1b through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Coinranking account through Composio's Coinranking MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Coinranking with

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

## TL;DR

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

The Coinranking MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Coinranking account. It provides structured and secure access to real-time and historical cryptocurrency market data, so your agent can perform actions like tracking prices, analyzing trends, fetching coin stats, and surfacing trending cryptocurrencies on your behalf.
- Real-time coin price tracking: Instantly access up-to-date prices for thousands of cryptocurrencies, letting your agent monitor the market or retrieve coin values on demand.
- Historical performance analysis: Retrieve and analyze historical price data for any coin, so your agent can chart trends and compare past performances.
- Global market overview: Get comprehensive statistics about the entire crypto market, including total market cap, volume, and dominance, all via your agent.
- Discover trending assets: Surface the most popular and trending coins based on user engagement, helping your agent highlight coins gaining traction right now.
- Reference currencies and tags management: Let your agent fetch supported fiat and crypto reference currencies, and retrieve all canonical tags for advanced filtering and categorization.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `COINRANKING_GET_COIN_HISTORY` | Get Coin History | Tool to retrieve historical price data for a specific coin over a time period. use when you need to analyze past performance of a coin; call after confirming its uuid. |
| `COINRANKING_GET_COINS` | Get Coins | Tool to retrieve a list of all coins with optional filters and pagination. use when you need to fetch coins matching specific criteria and paginate through results. |
| `COINRANKING_GET_REFERENCE_CURRENCIES` | Get Reference Currencies | Tool to retrieve a list of all reference currencies with optional pagination. use when you need supported fiat or crypto denominators for price conversions. |
| `COINRANKING_GET_STATS` | Get Global Crypto Market Stats | Tool to retrieve global cryptocurrency market statistics. use when you need an overview of the entire crypto market. |
| `COINRANKING_GET_TAGS` | Get Tags | Tool to fetch all coin tags. use when you need the canonical list of tags after authenticating. |
| `COINRANKING_GET_TRENDING_COINS` | Get Trending Coins | Tool to retrieve a list of trending coins ranked by user engagement and popularity. use when you need up-to-date trending coin data for analysis or display. |

## Supported Triggers

None listed.

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

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

url = session.mcp.url
```

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

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

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

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

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

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

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

## Related Toolkits

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- [Eodhd apis](https://composio.dev/toolkits/eodhd_apis) - Eodhd apis delivers comprehensive financial data, including live and historical stock prices, via robust APIs. Easily access reliable, up-to-date market insights to power your apps, dashboards, and analytics.
- [Fidel api](https://composio.dev/toolkits/fidel_api) - Fidel api is a secure platform for linking payment cards to web and mobile apps. It enables real-time card transaction monitoring and event-based automation for businesses.
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- [Finmei](https://composio.dev/toolkits/finmei) - Finmei is an invoicing tool that simplifies billing, invoice management, and expense tracking. Ideal for automating and organizing your business finances in one place.
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- [Fixer io](https://composio.dev/toolkits/fixer_io) - Fixer.io is a lightweight API for real-time and historical foreign exchange rates. It makes global currency conversion fast, accurate, and hassle-free.
- [Flutterwave](https://composio.dev/toolkits/flutterwave) - Flutterwave is a global payments platform enabling businesses to accept and send payments across Africa and beyond. Its robust APIs simplify cross-border transactions and financial operations.

## Frequently Asked Questions

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

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

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

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

---
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