How to integrate Habitica MCP with LangChain

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Introduction

This guide walks you through connecting Habitica to LangChain using the Composio tool router. By the end, you'll have a working Habitica agent that can add a new daily task for exercise, create a challenge for team productivity, delete an outdated task from my challenge, create a tag for urgent work tasks through natural language commands.

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

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

TL;DR

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

The Habitica MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Habitica account. It provides structured and secure access to your tasks, challenges, and groups, so your agent can create tasks, manage challenges, organize groups, and automate productivity routines on your behalf.

  • Automated task creation and management: Let your agent create new tasks, set up habits, or add to-dos to keep your productivity on track—no manual entry needed.
  • Challenge and group organization: Easily create, edit, or delete Habitica challenges and groups so you can coordinate goals and activities with teams or friends.
  • Tag and webhook automation: Have your agent generate new tags for smarter task sorting or set up webhooks for real-time notifications when tasks change or are completed.
  • Subscription and group membership management: Direct your agent to check or cancel subscriptions, leave parties, or delete groups as your needs change.
  • Seamless challenge task updates: Effortlessly add or remove tasks within challenges, helping you keep group goals relevant and up to date.

Supported Tools & Triggers

Tools
Add Task to ChallengeTool to add a new task to a specified challenge.
Cancel SubscriptionAttempts to cancel the authenticated user's subscription.
Create ChallengeTool to create a new challenge.
Create Habitica GroupTool to create a Habitica party or guild.
Create TagTool to create a new tag.
Create TaskTool to create a new user task in Habitica.
Create WebhookTool to create a new webhook for taskActivity events.
Delete a Habitica ChallengeTool to delete a challenge.
Delete Challenge TaskTool to delete a specific task from a challenge.
Delete Habitica GroupTool to delete a Habitica group (guild) or leave a party.
Delete Habitica TagTool to delete a tag for the authenticated user.
Delete TaskTool to delete a Habitica task.
Get Habitica AchievementsTool to retrieve all available Habitica achievements.
Get ChallengeTool to retrieve details of a specific challenge.
Get Group ChallengesTool to retrieve challenges available in a specific group (guild, party, or tavern).
Get Challenge TaskTool to retrieve a specific task from any challenge.
Get Challenge TasksTool to get all tasks for a specified challenge.
Get ContentTool to retrieve global game content definitions.
Get Content By TypeTool to retrieve game content for a specified category.
Get EquipmentTool to retrieve the authenticated user’s equipped gear and costume.
Get GroupTool to retrieve details of a specific group.
Get Group MembersTool to retrieve members of a specific group.
Get Habitica GroupsTool to retrieve Habitica groups (guilds, parties, taverns).
Get NotificationsTool to retrieve notifications for the authenticated user.
Get PartyTool to retrieve the authenticated user's party details.
Get Party MembersTool to retrieve members of the authenticated user's party.
Get TagsTool to retrieve authenticated user's tags.
Get TasksTool to retrieve all tasks for the authenticated user.
Get User AchievementsTool to retrieve the authenticated user's achievements.
Get User ChallengesTool to retrieve challenges the authenticated user participates in.
Get User InventoryTool to retrieve the authenticated user's full inventory.
Get User ProfileTool to retrieve the authenticated user's profile information.
Get User Quest ProgressTool to retrieve the authenticated user's quest progress.
Get User StatsTool to retrieve the authenticated user's Habitica statistics.
Get User SubscriptionTool to retrieve the authenticated user's subscription details.
Get WebhooksTool to retrieve webhooks for the authenticated user.
Invite To GroupTool to invite users to a specific group.
Invite To PartyTool to invite users to the authenticated user's party.
Join ChallengeTool to join a challenge.
Leave ChallengeTool to leave a Habitica challenge.
Local LoginTool to authenticate a user via local credentials.
Local User RegistrationTool to register a new Habitica user via email and password.
Mark Notifications SeenTool to mark specific notifications as read.
Remove Party MemberTool to remove a member from your party.
Score TaskTool to score (check/uncheck) a Habitica task.
Social AuthTool to authenticate a user via a social provider.
Subscribe WebhookTool to enable (subscribe) an existing webhook by ID for the authenticated user.

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

What is Tool Router?

Composio's Tool Router 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 Tool Router

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

How the Tool Router works

The Tool Router 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

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

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.

Install dependencies

pip install composio-langchain langchain-mcp-adapters langchain python-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 is the core agent framework
  • python-dotenv loads environment variables

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

Import dependencies

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

Initialize Composio client

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")
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 Habitica tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

# Create Tool Router session for Habitica
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['habitica']
)

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

Configure the agent with the MCP URL

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

Set up interactive chat interface

conversation_history = []

print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Habitica 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")
What's happening:
  • We initialize an empty conversation_history list to maintain context across interactions
  • A while loop continuously accepts 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 ainvoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully

Run the application

if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • We call the main() function using asyncio.run() to start the application

Complete Code

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

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=['habitica']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "habitica-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 Habitica 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())

Conclusion

You've successfully built a LangChain agent that can interact with Habitica 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 Habitica MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Habitica MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Habitica MCP with Claude Agent SDK

Google ADK

Google ADK

Use Habitica MCP with Google ADK

Vercel AI SDK

Vercel AI SDK

Use Habitica MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Habitica MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Habitica MCP with LlamaIndex

CrewAI

CrewAI

Use Habitica MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Habitica MCP?

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

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

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

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