# How to integrate Ticktick MCP with Autogen ```json { "title": "How to integrate Ticktick MCP with Autogen", "toolkit": "Ticktick", "toolkit_slug": "ticktick", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/ticktick/framework/autogen", "markdown_url": "https://composio.dev/toolkits/ticktick/framework/autogen.md", "updated_at": "2026-05-12T10:28:27.341Z" } ``` ## Introduction This guide walks you through connecting Ticktick to AutoGen using the Composio tool router. By the end, you'll have a working Ticktick agent that can add a new task for tomorrow morning, complete all overdue tasks in your inbox, create a project called 'vacation planning' through natural language commands. This guide will help you understand how to give your AutoGen 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 - [OpenAI Agents SDK](https://composio.dev/toolkits/ticktick/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/ticktick/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/ticktick/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/ticktick/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/ticktick/framework/codex) - [OpenClaw](https://composio.dev/toolkits/ticktick/framework/openclaw) - [Hermes](https://composio.dev/toolkits/ticktick/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/ticktick/framework/cli) - [Google ADK](https://composio.dev/toolkits/ticktick/framework/google-adk) - [LangChain](https://composio.dev/toolkits/ticktick/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/ticktick/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/ticktick/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/ticktick/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/ticktick/framework/crew-ai) ## TL;DR Here's what you'll learn: - Get and set up your OpenAI and Composio API keys - Install the required dependencies for Autogen and Composio - Initialize Composio and create a Tool Router session for Ticktick - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Ticktick tools - Run a live chat loop where you ask the agent to perform Ticktick operations ## What is AutoGen? Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows. Key features include: - Multi-Agent Systems: Build collaborative agent workflows - MCP Workbench: Native support for Model Context Protocol tools - Streaming HTTP: Connect to external services through streamable HTTP - AssistantAgent: Pre-built agent class for tool-using assistants ## 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. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `TICKTICK_COMPLETE_TASK` | Complete Task | Marks a TickTick task as complete. Requires both the project_id and task_id, which can be obtained from TICKTICK_LIST_ALL_TASKS or TICKTICK_CREATE_TASK actions. This action is idempotent - completing an already-completed task will succeed without error. Completed tasks are removed from default/active views and appear only in completed task filters. | | `TICKTICK_CREATE_PROJECT` | Create Project | Create a new project (list) in TickTick. Projects organize tasks and notes. Use this to set up a new project with optional customizations like color, view mode, and type. The created project's ID can be used with other actions like TICKTICK_CREATE_TASK. | | `TICKTICK_CREATE_TASK` | Create Task | Tool to create a new task in TickTick. Use after you have task details such as title, dates, and optional reminders or subtasks. | | `TICKTICK_DELETE_PROJECT` | Delete TickTick Project | Permanently deletes a TickTick project by its ID. All tasks within the project will also be deleted. Note: This operation is idempotent - deleting a non-existent project ID returns success. Use TICKTICK_GET_USER_PROJECT to list available projects and their IDs before deletion. | | `TICKTICK_DELETE_TASK` | Delete Task | Tool to permanently delete a specific task — irreversible, no recovery. Use when you need to remove a task from a project after confirming both project and task IDs. Returns an empty data object on success; check status/success flags rather than response payload. When moving tasks between projects via create+delete, comments and history are lost. | | `TICKTICK_GET_PROJECT_BY_ID` | Get Project By ID | Tool to retrieve a specific TickTick project by its unique ID. Use when you need detailed information about a particular project after obtaining its project ID. | | `TICKTICK_GET_PROJECT_WITH_DATA` | Get project with data | Retrieve a project's associated data (incomplete tasks, columns). IMPORTANT: This endpoint only returns INCOMPLETE tasks. Completed tasks are automatically filtered out by the TickTick API. An empty tasks list means either the project has no tasks at all, or all tasks have been completed. For completed tasks, check the TickTick app or web interface directly. Columns are only present for kanban-style projects; list-view projects return an empty columns array. Join tasks to columns via each task's columnId field. For large projects, results may paginate at ~100 items per page — iterate all pages and deduplicate by taskId. Multiple tasks can share the same title; always use taskId for follow-up create, update, or delete calls. All filtering by name, tag, or other fields must be done client-side. Scope is project-only — Inbox and other projects are excluded. | | `TICKTICK_GET_TASK_BY_PROJECT_AND_ID` | Get Task By Project And ID | Tool to retrieve a specific TickTick task by project ID and task ID. Use when you need detailed information about a particular task within a project. | | `TICKTICK_GET_USER_PROJECT` | Get User Projects | Retrieves all projects accessible to the authenticated user, including personal and shared projects. Use this tool to list available projects before creating tasks or to get project IDs for other operations. Returns project metadata including name, color, view mode, and organization details. Always use returned projectId values (not project names) when calling TICKTICK_CREATE_TASK, TICKTICK_UPDATE_TASK, or TICKTICK_GET_PROJECT_WITH_DATA. The inbox project may not appear in results — omit projectId in TICKTICK_CREATE_TASK to target the inbox. Non-kanban projects return an empty columns array; check viewMode before assuming columns exist. | | `TICKTICK_LIST_ALL_TASKS` | List All Tasks | Tool to list all open/undone tasks across all user projects in one call. This is a composite operation that internally fetches all projects and aggregates their tasks. Use when you need a comprehensive view of pending work across the entire account. Note: Only returns open/undone tasks; completed task history is not available in TickTick OpenAPI v1. | | `TICKTICK_OAUTH2_AUTHORIZATION_STEP1` | Generate OAuth2 Authorization URL | Tool to generate the TickTick OAuth2 authorization URL. Use to redirect the user to obtain the authorization code (step 1). Re-run this tool if downstream TickTick calls return HTTP 401 (expired/invalid token) to obtain a fresh authorization code. | | `TICKTICK_UPDATE_PROJECT` | Update Project | Tool to update an existing project. Use when you need to modify project details like name, color, sort order, view mode, or kind after selecting a project ID. | | `TICKTICK_UPDATE_TASK` | Update Task | Tool to update an existing task. Use after confirming the taskId and projectId. Omitting optional fields resets them to null — include all existing field values in every payload. Cannot move a task to a different project; use TICKTICK_CREATE_TASK + TICKTICK_DELETE_TASK instead. Fields outside the input schema (e.g., columnId, assignee) are silently ignored. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Ticktick MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Ticktick. Instead of manually wiring Ticktick APIs, OAuth, and scopes yourself, you get a structured, tool-based interface that an LLM can call safely. 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 You will need: - A Composio API key - An OpenAI API key (used by Autogen's OpenAIChatCompletionClient) - A Ticktick account you can connect to Composio - Some basic familiarity with Autogen and Python async ### 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 Install Composio, Autogen extensions, and dotenv. What's happening: - composio connects your agent to Ticktick via MCP - autogen-agentchat provides the AssistantAgent class - autogen-ext-openai provides the OpenAI model client - autogen-ext-tools provides MCP workbench support ```bash pip install composio python-dotenv pip install autogen-agentchat autogen-ext-openai autogen-ext-tools ``` ### 3. Set up environment variables Create a .env file in your project folder. What's happening: - COMPOSIO_API_KEY is required to talk to Composio - OPENAI_API_KEY is used by Autogen's OpenAI client - USER_ID is how Composio identifies which user's Ticktick connections to use ```bash COMPOSIO_API_KEY=your-composio-api-key OPENAI_API_KEY=your-openai-api-key USER_ID=your-user-identifier@example.com ``` ### 4. Import dependencies and create Tool Router session What's happening: - load_dotenv() reads your .env file - Composio(api_key=...) initializes the SDK - create(...) creates a Tool Router session that exposes Ticktick tools - session.mcp.url is the MCP endpoint that Autogen will connect to ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from autogen_agentchat.agents import AssistantAgent from autogen_ext.models.openai import OpenAIChatCompletionClient from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams load_dotenv() async def main(): # Initialize Composio and create a Ticktick session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["ticktick"] ) url = session.mcp.url ``` ### 5. Configure MCP parameters for Autogen Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for. What's happening: - url points to the Tool Router MCP endpoint from Composio - timeout is the HTTP timeout for requests - sse_read_timeout controls how long to wait when streaming responses - terminate_on_close=True cleans up the MCP server process when the workbench is closed ```python # Configure MCP server parameters for Streamable HTTP server_params = StreamableHttpServerParams( url=url, timeout=30.0, sse_read_timeout=300.0, terminate_on_close=True, headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")} ) ``` ### 6. Create the model client and agent What's happening: - OpenAIChatCompletionClient wraps the OpenAI model for Autogen - McpWorkbench connects the agent to the MCP tools - AssistantAgent is configured with the Ticktick tools from the workbench ```python # Create model client model_client = OpenAIChatCompletionClient( model="gpt-5", api_key=os.getenv("OPENAI_API_KEY") ) # Use McpWorkbench as context manager async with McpWorkbench(server_params) as workbench: # Create Ticktick assistant agent with MCP tools agent = AssistantAgent( name="ticktick_assistant", description="An AI assistant that helps with Ticktick operations.", model_client=model_client, workbench=workbench, model_client_stream=True, max_tool_iterations=10 ) ``` ### 7. Run the interactive chat loop What's happening: - The script prompts you in a loop with You: - Autogen passes your input to the model, which decides which Ticktick tools to call via MCP - agent.run_stream(...) yields streaming messages as the agent thinks and calls tools - Typing exit, quit, or bye ends the loop ```python print("Chat started! Type 'exit' or 'quit' to end the conversation.\n") print("Ask any Ticktick related question or task to the agent.\n") # Conversation loop while True: user_input = input("You: ").strip() if user_input.lower() in ["exit", "quit", "bye"]: print("\nGoodbye!") break if not user_input: continue print("\nAgent is thinking...\n") # Run the agent with streaming try: response_text = "" async for message in agent.run_stream(task=user_input): if hasattr(message, "content") and message.content: response_text = message.content # Print the final response if response_text: print(f"Agent: {response_text}\n") else: print("Agent: I encountered an issue processing your request.\n") except Exception as e: print(f"Agent: Sorry, I encountered an error: {str(e)}\n") ``` ## Complete Code ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from autogen_agentchat.agents import AssistantAgent from autogen_ext.models.openai import OpenAIChatCompletionClient from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams load_dotenv() async def main(): # Initialize Composio and create a Ticktick session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["ticktick"] ) url = session.mcp.url # Configure MCP server parameters for Streamable HTTP server_params = StreamableHttpServerParams( url=url, timeout=30.0, sse_read_timeout=300.0, terminate_on_close=True, headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")} ) # Create model client model_client = OpenAIChatCompletionClient( model="gpt-5", api_key=os.getenv("OPENAI_API_KEY") ) # Use McpWorkbench as context manager async with McpWorkbench(server_params) as workbench: # Create Ticktick assistant agent with MCP tools agent = AssistantAgent( name="ticktick_assistant", description="An AI assistant that helps with Ticktick operations.", model_client=model_client, workbench=workbench, model_client_stream=True, max_tool_iterations=10 ) print("Chat started! Type 'exit' or 'quit' to end the conversation.\n") print("Ask any Ticktick related question or task to the agent.\n") # Conversation loop while True: user_input = input("You: ").strip() if user_input.lower() in ['exit', 'quit', 'bye']: print("\nGoodbye!") break if not user_input: continue print("\nAgent is thinking...\n") # Run the agent with streaming try: response_text = "" async for message in agent.run_stream(task=user_input): if hasattr(message, 'content') and message.content: response_text = message.content # Print the final response if response_text: print(f"Agent: {response_text}\n") else: print("Agent: I encountered an issue processing your request.\n") except Exception as e: print(f"Agent: Sorry, I encountered an error: {str(e)}\n") if __name__ == "__main__": asyncio.run(main()) ``` ## Conclusion You now have an Autogen assistant wired into Ticktick through Composio's Tool Router and MCP. From here you can: - Add more toolkits to the toolkits list, for example notion or hubspot - Refine the agent description to point it at specific workflows - Wrap this script behind a UI, Slack bot, or internal tool Once the pattern is clear for Ticktick, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build Ticktick MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/ticktick/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/ticktick/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/ticktick/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/ticktick/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/ticktick/framework/codex) - [OpenClaw](https://composio.dev/toolkits/ticktick/framework/openclaw) - [Hermes](https://composio.dev/toolkits/ticktick/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/ticktick/framework/cli) - [Google ADK](https://composio.dev/toolkits/ticktick/framework/google-adk) - [LangChain](https://composio.dev/toolkits/ticktick/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/ticktick/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/ticktick/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/ticktick/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/ticktick/framework/crew-ai) ## Related Toolkits - [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly. - [Notion](https://composio.dev/toolkits/notion) - Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place. - [Airtable](https://composio.dev/toolkits/airtable) - Airtable combines the flexibility of spreadsheets with the power of a database for easy project and data management. Teams use Airtable to organize, track, and collaborate with custom views and automations. - [Asana](https://composio.dev/toolkits/asana) - Asana is a collaborative work management platform for teams to organize and track projects. It streamlines teamwork, boosts productivity, and keeps everyone aligned on goals. - [Google Tasks](https://composio.dev/toolkits/googletasks) - Google Tasks is a to-do list and task management tool integrated into Gmail and Google Calendar. It helps you organize, track, and complete tasks across your Google ecosystem. - [Linear](https://composio.dev/toolkits/linear) - Linear is a modern issue tracking and project planning tool for fast-moving teams. It helps streamline workflows, organize projects, and boost productivity. - [Jira](https://composio.dev/toolkits/jira) - Jira is Atlassian’s platform for bug tracking, issue tracking, and agile project management. It helps teams organize work, prioritize tasks, and deliver projects efficiently. - [Clickup](https://composio.dev/toolkits/clickup) - ClickUp is an all-in-one productivity platform for managing tasks, docs, goals, and team collaboration. It streamlines project workflows so teams can work smarter and stay organized in one place. - [Monday](https://composio.dev/toolkits/monday) - Monday.com is a customizable work management platform for project planning and collaboration. It helps teams organize tasks, automate workflows, and track progress in real time. - [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time. - [Agiled](https://composio.dev/toolkits/agiled) - Agiled is an all-in-one business management platform for CRM, projects, and finance. It helps you streamline workflows, consolidate client data, and manage business processes in one place. - [Ascora](https://composio.dev/toolkits/ascora) - Ascora is a cloud-based field service management platform for service businesses. It streamlines scheduling, invoicing, and customer operations in one place. - [Basecamp](https://composio.dev/toolkits/basecamp) - Basecamp is a project management and team collaboration tool by 37signals. It helps teams organize tasks, share files, and communicate efficiently in one place. - [Beeminder](https://composio.dev/toolkits/beeminder) - Beeminder is an online goal-tracking platform that uses monetary pledges to keep you motivated. Stay accountable and hit your targets with real financial incentives. - [Boxhero](https://composio.dev/toolkits/boxhero) - Boxhero is a cloud-based inventory management platform for SMBs, offering real-time updates, barcode scanning, and team collaboration. It helps businesses streamline stock tracking and analytics for smarter inventory decisions. - [Breathe HR](https://composio.dev/toolkits/breathehr) - Breathe HR is cloud-based HR software for SMEs to manage employee data, absences, and performance. It simplifies HR admin, making it easy to keep employee records accurate and up to date. - [Breeze](https://composio.dev/toolkits/breeze) - Breeze is a project management platform designed to help teams plan, track, and collaborate on projects. It streamlines workflows and keeps everyone on the same page. - [Bugherd](https://composio.dev/toolkits/bugherd) - Bugherd is a visual feedback and bug tracking tool for websites. It helps teams and clients report website issues directly on live sites for faster fixes. - [Canny](https://composio.dev/toolkits/canny) - Canny is a platform for managing customer feedback and feature requests. It helps teams prioritize product decisions based on real user insights. - [Chmeetings](https://composio.dev/toolkits/chmeetings) - Chmeetings is a church management platform for events, members, donations, and volunteers. It streamlines church operations and improves community engagement. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Ticktick MCP? 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. ### Can I use Tool Router MCP with Autogen? Yes, you can. Autogen 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. ### Can I manage the permissions and scopes for Ticktick while using Tool Router? 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. ### 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 Ticktick data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)