How to integrate Swaggerhub MCP with LangChain

This guide walks you through connecting Swaggerhub to LangChain using the Composio tool router. By the end, you'll have a working Swaggerhub agent that can list all apis i have access to, create a new api named petstore, update the description for your orders api through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Swaggerhub account through Composio's Swaggerhub MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Swaggerhub is a collaborative API design and documentation platform built on OpenAPI. It accelerates API delivery, quality, and teamwork with powerful standards and workflow tools.

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Introduction

This guide walks you through connecting Swaggerhub to LangChain using the Composio tool router. By the end, you'll have a working Swaggerhub agent that can list all apis i have access to, create a new api named petstore, update the description for your orders api through natural language commands.

This guide will help you understand how to give your LangChain agent real control over a Swaggerhub account through Composio's Swaggerhub MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Swaggerhub with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

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

The Swaggerhub MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Swaggerhub account. It provides structured and secure access so your agent can perform Swaggerhub operations on your behalf.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step10 STEPS
1

Prerequisites

Before starting this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI API key
  • Basic familiarity with Python and async programming
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard 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.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

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

Install the required packages for LangChain with MCP support.

What's happening:

  • @composio/langchain provides Composio integration for LangChain
  • @langchain/mcp-adapters enables MCP client connections
  • @langchain/core is the core agent framework
  • dotenv/config loads environment variables
4

Set up environment variables

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

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
5

Import dependencies

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();
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv/config import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Swaggerhub functionality through MCP
6

Initialize Composio client

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()
    });
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 Swaggerhub tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding
7

Create a Tool Router session

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

const url = session.mcp.url;
What's happening:
  • We're creating a Tool Router session that gives your agent access to Swaggerhub 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 Swaggerhub tools as needed
8

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "swaggerhub-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 });
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Swaggerhub MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • getTools() retrieves all available Swaggerhub tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model
9

Set up interactive chat interface

let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Swaggerhub 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);
    });
What's happening:
  • We initialize an empty conversationHistory list to maintain context across interactions
  • A readline interface is used to continuously accept user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the invoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully
10

Run the application

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
What's happening:
  • We call the main() function to start the application

Complete Code

Here's the complete code to get you started with Swaggerhub and LangChain:

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: ['swaggerhub']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "swaggerhub-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 Swaggerhub 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 Swaggerhub 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.
TOOLS

Supported Tools

Every Swaggerhub action and event your agent gets out of the box.

Add Access Control for Teams

Tool to assign access control roles to teams on a SwaggerHub resource.

Add Access Control for Users

Tool to assign access control roles to users on a SwaggerHub resource.

Delete Table of Contents Entry

Tool to delete a table of contents entry from SwaggerHub portal.

Get Access Control Users

Tool to retrieve the list of users assigned access control on a SwaggerHub resource.

Get API Default Version

Tool to get the default version identifier of a SwaggerHub API.

Get API Versions

Tool to retrieve a list of API versions for a specific API in SwaggerHub.

Get Consumer Products

Tool to get a list of products that are visible to the consumer in a SwaggerHub portal.

Get API Definition

Tool to get the OpenAPI definition of a specified API version from SwaggerHub.

Get Domain Default Version

Tool to retrieve the default version identifier of a SwaggerHub domain.

Get domain definition

Tool to retrieve the OpenAPI definition of a specified domain version from SwaggerHub.

Get Domain JSON Definition

Tool to retrieve the OpenAPI definition for a specified domain version in JSON format.

Get Domain Lifecycle Settings

Tool to get the published status for a specific domain and version in SwaggerHub.

Get Domain Private Settings

Tool to retrieve the visibility (public or private) of a domain version in SwaggerHub.

Get Domain Versions

Tool to get a list of domain versions from SwaggerHub.

Get Domain YAML Definition

Tool to retrieve the OpenAPI definition for a specified domain version in YAML format from SwaggerHub.

Get JSON API Definition

Tool to download OpenAPI definition as a JSON file from SwaggerHub Portal API.

Get JSON Definition

Tool to get the OpenAPI definition for a specified API version in JSON format.

Get lifecycle settings

Tool to get the published status for the specified API and version.

Get Organization Members

Tool to retrieve a list of organization members and their roles from SwaggerHub.

Get User Organizations

Tool to get organizations for a user.

Get Organization Projects V2

Tool to get all projects of an organization in SwaggerHub.

Get Owner APIs

Tool to get a list of APIs for a specified owner in SwaggerHub.

Get owner domains

Tool to retrieve domains owned by a specific SwaggerHub user or organization.

Get Portal

Tool to retrieve information about a portal.

Get Portal Access Requests

Tool to retrieve access requests for a portal in SwaggerHub.

Get Portal Attachment

Tool to get informational attachment metadata from SwaggerHub Portal.

Get Portal Product

Tool to retrieve detailed information about a specific product resource.

Get Portal Products

Tool to get products for a specific portal that match your criteria.

Get Portals

Tool to search for available portals.

Get Portal Templates

Tool to get templates for a specific portal that match your criteria.

Get API Version Private Settings

Tool to get the visibility (public or private) of an API version.

List Resource Types and Roles

Tool to list available resource types and assignable roles for each in a SwaggerHub organization.

Get Templates

Tool to retrieve a list of templates for an owner in SwaggerHub.

Get User Roles

Tool to retrieve all roles assigned to a user across organization resources in SwaggerHub.

Get YAML API Definition

Tool to download OpenAPI definition as a YAML file from SwaggerHub Portal API.

Get YAML Definition

Tool to get the OpenAPI definition in YAML format for the specified API version from SwaggerHub.

List Attachments

Tool to retrieve all attachments for a portal or product.

Remove Access Control for Teams

Tool to remove access control for teams from a SwaggerHub resource.

Remove Access Control For Users

Tool to remove access control for users from a SwaggerHub organizational resource.

Remove Organization Members

Tool to remove members from a SwaggerHub organization.

Search APIs

Tool to search SwaggerHub APIs.

Search APIs and Domains

Tool to search SwaggerHub APIs, domains, and templates.

Search Domains

Tool to search SwaggerHub domains.

Search Published Portal

Tool to search published portal content.

Update Access Control for Teams

Tool to update access control roles for teams on a SwaggerHub resource.

Update Access Control for Users

Tool to update access control roles for users on a SwaggerHub resource.

Update Access Control for Teams

Tool to update access control for teams on a SwaggerHub resource.

Update Access Control Users

Tool to update access control roles for users on a SwaggerHub resource.

Update Portal

Tool to update specific portal information in SwaggerHub.

FRAMEWORKS

How to build Swaggerhub MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Swaggerhub MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Swaggerhub MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Swaggerhub MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Swaggerhub MCP with Claude Cowork

Codex logo

Codex

Use Swaggerhub MCP with Codex

OpenClaw logo

OpenClaw

Use Swaggerhub MCP with OpenClaw

Hermes logo

Hermes

Use Swaggerhub MCP with Hermes

CLI logo

CLI

Use Swaggerhub MCP with CLI

Google ADK logo

Google ADK

Use Swaggerhub MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Swaggerhub MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Swaggerhub MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Swaggerhub MCP with LlamaIndex

CrewAI logo

CrewAI

Use Swaggerhub MCP with CrewAI

FAQ

Frequently asked questions

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

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 Swaggerhub tools.

Yes, absolutely. You can configure which Swaggerhub 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.

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 Swaggerhub data and credentials are handled as safely as possible.

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A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

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Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

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