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How to integrate Ticktick MCP with CrewAI

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TickTick is a cross-platform task management and to-do list app. It helps you organize tasks, set reminders, and stay on top of your schedule.

22 Tools

Introduction

This guide walks you through connecting Ticktick to CrewAI using the Composio tool router. By the end, you'll have a working Ticktick agent that can create and update tasks, complete and move tasks, manage projects, add task comments, and filter tasks through natural language commands.

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

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

Also integrate Ticktick with

Claude CodeClaude CoworkOpenAI Agents SDKClaude Agent SDKCodexOpenClawHermesAtomic AgentGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexPydantic AIAutoGen

TL;DR

Here's what you'll learn:
  • Get a Composio API key and configure your Ticktick connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Ticktick
  • Build a conversational loop where your agent can execute Ticktick operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

What is the Ticktick MCP server, and what's possible with it?

The Ticktick MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Ticktick account. It provides structured and secure access to your task lists and projects, so your agent can create, manage, and organize tasks, complete or delete items, and streamline your productivity workflows automatically.

  • Automated task creation and editing: Let your agent add new tasks, set deadlines, and update task details across your Ticktick projects with ease.
  • Project management and organization: Direct your agent to create, retrieve, or delete entire projects, keeping your workspace tidy and aligned with your priorities.
  • Seamless task completion and cleanup: Ask your agent to mark tasks as complete or delete tasks you've finished or no longer need, helping you stay on top of your to-do list.
  • Comprehensive project data retrieval: Have your agent fetch detailed project information, including all associated tasks and columns, for quick overviews or reporting.
  • Effortless OAuth2 authentication management: Benefit from a streamlined, agent-guided authorization flow that securely connects your Ticktick account with minimal friction.

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 step08 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Ticktick connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python
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

bash
pip install composio crewai crewai-tools[mcp] python-dotenv
What's happening:
  • composio connects your agent to Ticktick via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools[mcp] includes MCP helpers
  • python-dotenv loads environment variables from .env
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_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 with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model
5

Import dependencies

python
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Ticktick MCP URL
6

Create a Composio Tool Router session for Ticktick

python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["ticktick"])

url = session.mcp.url
What's happening:
  • You create a Ticktick only session through Composio
  • Composio returns an MCP HTTP URL that exposes Ticktick tools
7

Initialize the MCP Server

python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
What's Happening:
  • Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
  • MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
  • Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
  • Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
  • Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.
8

Create a CLI Chatloop and define the Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")

conversation_context = ""

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[agent], tasks=[task], verbose=False)
    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's Happening:
  • Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
  • Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
  • Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
  • Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
  • Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
  • Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.

Complete Code

Here's the complete code to get you started with Ticktick and CrewAI:

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["ticktick"],
)
url = session.mcp.url

# Configure LLM
llm = LLM(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY"),
)

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end.\n")

    conversation_context = ""

    while True:
        user_input = input("You: ").strip()

        if user_input.lower() in ["exit", "quit", "bye"]:
            print("\nGoodbye!")
            break

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

Conclusion

You now have a CrewAI agent connected to Ticktick through Composio's Tool Router. The agent can perform Ticktick operations through natural language commands.

Next steps:

  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations
TOOLS

Supported Tools

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

Add Task Comment

Add a discussion comment to a task in a TickTick project.

Batch Create Or Update Tasks

Create and update up to 50 TickTick tasks per operation in one request.

Complete Task

Mark a TickTick task as complete using its project ID and task ID.

Create Column

Create a named column in an existing TickTick project.

Create Project

Create a new project (list) in TickTick.

Create Task

Tool to create a new task in TickTick.

Delete TickTick Project

Permanently deletes a TickTick project by its ID.

Delete Task

Tool to permanently delete a specific task — irreversible, no recovery.

Filter Tasks

Return up to 200 tasks matching project, start-date, priority, tag, kind, and status filters.

Get Project By ID

Tool to retrieve a specific TickTick project by its unique ID.

Get project with data

Retrieve a TickTick project's metadata, undone tasks, and columns by project ID.

Get Task By Project And ID

Tool to retrieve a specific TickTick task by project ID and task ID.

Get User Projects

Retrieves projects accessible to the authenticated user, including their IDs and metadata such as name, color, view mode, and organization details.

List All Tasks

List open tasks across TickTick projects, with project context.

List Completed Tasks

Return up to 200 completed tasks, optionally filtered by project and completion date.

List Project Members

List the users who belong to a TickTick project.

List Tags

List the tags available to the connected TickTick account.

List Task Comments

List discussion comments attached to a task in a TickTick project.

Move Tasks

Move one or more existing tasks between TickTick projects.

Generate OAuth2 Authorization URL

Tool to generate the TickTick OAuth2 authorization URL.

Update Project

Tool to update an existing project.

Update Task

Updates an existing TickTick task identified by task ID and project ID, with optional task details such as dates, reminders, recurrence, priority, and checklist items.

FRAMEWORKS

How to build Ticktick MCP Agent with another framework

Claude Code logo

Claude Code

Use Ticktick MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Ticktick MCP with Claude Cowork

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Ticktick MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Ticktick MCP with Claude Agent SDK

Codex logo

Codex

Use Ticktick MCP with Codex

OpenClaw logo

OpenClaw

Use Ticktick MCP with OpenClaw

Hermes logo

Hermes

Use Ticktick MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Ticktick MCP with Atomic Agent

Google ADK logo

Google ADK

Use Ticktick MCP with Google ADK

LangChain logo

LangChain

Use Ticktick MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Ticktick MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Ticktick MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Ticktick MCP with LlamaIndex

Pydantic AI logo

Pydantic AI

Use Ticktick MCP with Pydantic AI

AutoGen logo

AutoGen

Use Ticktick MCP with AutoGen

FAQ

Frequently asked questions

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

Yes, you can. CrewAI 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 Ticktick tools.

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

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