by greirson
Enhance productivity with Todoist integration for task, project, and comment management using advanced API support and b
Connects to your Todoist account to manage tasks, projects, and labels directly through AI conversations. Lets you create, update, and organize your todo items using natural language.
Todoist is a community-built MCP server published by greirson that provides AI assistants with tools and capabilities via the Model Context Protocol. Enhance productivity with Todoist integration for task, project, and comment management using advanced API support and b It is categorized under productivity.
You can install Todoist in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
Todoist is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
According to our notes, Todoist benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
We wired Todoist into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Todoist reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Todoist is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
I recommend Todoist for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
We wired Todoist into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
We evaluated Todoist against two servers with overlapping tools; this profile had the clearer scope statement.
According to our notes, Todoist benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Todoist has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
We evaluated Todoist against two servers with overlapping tools; this profile had the clearer scope statement.
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An MCP (Model Context Protocol) server that connects Claude with Todoist for complete task and project management through natural language.
claude mcp add todoist -e TODOIST_API_TOKEN=your_token -- npx @greirson/mcp-todoist
Add to your MCP client config (claude_desktop_config.json, ~/.claude.json, etc.):
{
"mcpServers": {
"todoist": {
"command": "npx",
"args": ["@greirson/mcp-todoist"],
"env": {
"TODOIST_API_TOKEN": "your_api_token_here"
}
}
}
}
Config locations:
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.json~/.claude.jsonDry-run mode allows you to test operations and automations without making any real changes to your Todoist workspace. This is perfect for testing, debugging, learning the API, or validating automation scripts before running them for real.
Add DRYRUN=true to your environment configuration:
{
"mcpServers": {
"todoist": {
"command": "npx",
"args": ["@greirson/mcp-todoist"],
"env": {
"TODOIST_API_TOKEN": "your_api_token_here",
"DRYRUN": "true"
}
}
}
}
[DRY-RUN] prefixesWith dry-run mode enabled, operations show what would happen:
You: "Create a task called 'Test Task' in my Work project"
Response:
[DRY-RUN] Dry-run mode enabled - mutations will be simulated
[DRY-RUN] Would create task: "Test Task" in project 2203306141, section none
Task created successfully (simulated):
ID: 100001
Title: Test Task
Project: Work (2203306141)
Priority: 4 (Normal)
All 19 MCP tools support dry-run mode:
Remove the DRYRUN environment variable or set it to false, then restart Claude Desktop to return to normal operation mode.
The server provides 19 MCP tools for complete Todoist management:
| Tool | Actions | Description |
|---|---|---|
todoist_task | create, get, update, delete, complete, reopen, quick_add | Complete task management |
todoist_task_bulk | bulk_create, bulk_update, bulk_delete, bulk_complete | Efficient multi-task operations |
todoist_subtask | create, bulk_create, convert, promote, hierarchy | Hierarchical task management |
todoist_project | create, get, update, delete, archive, collaborators | Project CRUD and sharing |
todoist_project_ops | reorder, move_to_parent, get_archived | Advanced project operations |
todoist_section | create, get, update, delete, move, reorder, archive | Section management |
todoist_label | create, get, update, delete, stats | Label management with analytics |
todoist_comment | create, get, update, delete | Task/project comments |
todoist_reminder | create, get, update, delete | Reminder management (Pro) |
todoist_filter | create, get, update, delete | Custom filters (Pro) |
todoist_collaboration | invitations, notifications, workspace operations | Team collaboration features |
todoist_user | info, productivity_stats, karma_history | User profile and stats |
todoist_utility | test_connection, test_features, test_performance, find/merge duplicates | Testing and utilities |
todoist_activity | get_log, get_events, get_summary | Activity audit trail |
todoist_task_ops | move, reorder, close | Advanced task operations |
todoist_completed | get, get_all, get_stats | Completed task retrieval |
todoist_backup | list, download | Automatic backup access |
todoist_notes | create, get, update, delete | Project notes (collaborators) |
todoist_shared_labels | create, get, rename, remove | Workspace labels (Business) |
For detailed tool documentation with parameters and examples, see TOOLS_REFERENCE.md.
"No Todoist projects found" or connection errors:
MCP server not loading:
npm list -g @greirson/mcp-todoistmcp-todoist binary: /Users/USERNAME/.npm-global/bin/mcp-todoistPermission errors:
mkdir -p ~/.config"Show me all my projects"
"Create a new project called 'Work Tasks'"
"Create a section called 'In Progress' in project 12345"
"Show me sections in the Work Tasks project"
"Create task 'Team Meeting' in project 12345"
"Add task 'Review PR' due tomorrow with labels ['Code Review', 'Urgent']"
"Create high priority task with deadline 2024-12-25"
"Update meeting task to be in section 67890"
"Mark the PR review task as complete"
# Task duration for time blocking
"Create task 'Deep work session' with 90 minute duration"
"Update task 'Meeting' to have a 2 day duration"
# Task identification by ID (more reliable than name search)
"Get task with ID 1234567890"
"Update task ID 1234567890 to priority 4"
"Complete task with ID 1234567890"
"Reopen task with ID 1234567890"
"Delete task ID 1234567890"
The Quick Add tool parses natural language text like the Todoist app, supporting multiple features in a single command:
"Quick add: Buy groceries tomorrow #Shopping @errands p1"
"Quick add: Review PR next Monday #Work @code-review p2 //Check error handling"
"Quick add: Call mom {deadline in 3 days}"
"Quick add: Team meeting today at 2pm #Work @meetings with reminder 1 hour before"
Quick Add Syntax:
#ProjectName (no spaces in project names)@label (e.g., "@urgent", "@work")+name (for shared projects)p1 (urgent), p2, p3, p4 (lowest){in 3 days} or {March 15}//your description here (must be at the end)"Create subtask 'Prepare agenda' under task 'Team Meeting'"
"Create multiple subtasks for 'Launch Project': 'Design UI', 'Write tests', 'Deploy'"
"Convert task 'Code Review' to a subtask of 'Release v2.0'"
"Promote subtask 'Bug Fix' to a main task"
"Show me
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Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.