MCP100 verdict
Not currently recommended. First-party evidence supports Shortlist admission; this is not a Recommended-tier security certification.
MCP100 Assessment
Editorial verdict
Reviewed October 19, 2026
Task Fit
Mapped
Specialized workflows
Trust
Status warning
Shortlist evidence is sufficient for identity, setup and task value; authenticated runtime tool-schema measurement and exhaustive security certification remain out of scope.
Maintenance
Date unavailable
No dated repository or package update is currently stored.
Popularity
Signals available
Visible usage signals are shown for discovery only, not as proof of safety.
Evidence scope
561 MCP repository stars
17.3k package downloads / 30 days
Repository identity: Doist/todoist-mcp
Package identity: @doist/todoist-mcp · version 13.6.1
Stars observed October 20, 2026 · Downloads observed October 20, 2026
Current first-party Todoist MCP implementation repository with source code; stars are MCP-specific repository evidence.
Exact MCP-specific npm package identity verified against the first-party repository.
Publisher activity observed October 20, 2026
Current source snapshot
Source relationship: First-party MCP
Reviewed October 19, 2026
Evidence-backed setup
Choose your MCP client. A client connects to the MCP server; the language model is selected inside that client. Only stored, source-backed configurations are shown.
Transport not recorded
Complete client-specific setup, verification and removal are not documented in this reviewed source.
Publisher-documented setup is not the same as MCP100 execution testing. “MCP100 logic checked” means the stored configuration shape was reviewed, not that third-party MCP software was run.
Evidence checked 2026-10-20
Type-appropriate, source-backed setup for this mcp server profile.
Loading optional publisher installation details…
{"url":"https://ai.todoist.net/mcp"}Capability
Todoist MCP is a first-party MCP for manage todoist tasks and projects from an mcp-compatible assistant. Authentication/setup: OAuth. Task and project changes are real writes under the authenticated user's permissions; confirm bulk edits, moves, or deletions.
Official docs establish the hosted MCP and task/project capabilities but do not publish a stable exact tool inventory.
Not measured yet
Estimated token footprint of the MCP tool schemas exposed to the agent.
https://ai.todoist.net/mcp
Reviewed access
Reviewed sources
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Todoist is listed as First-party MCP in MCP100’s current evidence.
Current official resources:
From the publisher README
Original client setup and configuration retained from the publisher documentation.
Publisher-documented clients
These names appear in the publisher's installation documentation. MCP100-verified configurations are shown separately above when available.
You can run the MCP server directly with npx:
npx @doist/todoist-mcp
The Todoist MCP server is available as a streamable HTTP service for easy integration with various AI clients:
Primary URL (Streamable HTTP): https://ai.todoist.net/mcp
https://ai.todoist.net/mcp and complete OAuth authenticationCreate a configuration file:
~/.cursor/mcp.json.cursor/mcp.json{
"mcpServers": {
"todoist": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://ai.todoist.net/mcp"]
}
}
}
Then enable the server in Cursor settings if prompted.
The fastest setup is the official Todoist plugin, which wires up the MCP server for you:
/plugin marketplace add doist/todoist-mcp
/plugin install todoist@doist
OAuth runs in your browser the first time you use a Todoist tool. See Anthropic's plugin docs for more.
If you'd rather configure the MCP server manually, run:
claude mcp add --transport http todoist https://ai.todoist.net/mcp
Then launch claude, execute /mcp, and select the todoist MCP server to authenticate.
{
"servers": {
"todoist": {
"type": "http",
"url": "https://ai.todoist.net/mcp"
}
}
}
npx -y mcp-remote https://ai.todoist.net/mcp
For more details on setting up and using the MCP server, including creating custom servers, see docs/mcp-server.md.
After cloning and setting up the repository:
npm start - Build and run the MCP inspector for testingnpm run dev - Development mode with auto-rebuild and restartnpm run tool:list - List available tools for direct executionnpm run tool -- <tool-name> '<json-args>' - Run a tool directly without MCPWhen using npm run tool, include -- before tool arguments so npm forwards them to scripts/run-tool.ts.
Example check before write operations:
npm run tool -- user-info '{}'
This confirms which Todoist account the current TODOIST_API_KEY is connected to.
run-tool uses TODOIST_API_KEY from your .env file (created from .env.example by npm run setup). Use a test account or a temporary project when running write operations to avoid modifying real data.
Original product, capability, tool, and usage documentation from the MCP publisher. Installation sections appear under Install & Agents.
Library for connecting AI agents to Todoist. Includes tools that can be integrated into LLMs, enabling them to access and modify a Todoist account on the user's behalf.
These tools can be used both through an MCP server, or imported directly in other projects to integrate them to your own AI conversational interfaces.
npm install @doist/todoist-mcp
Here's an example using Vercel's AI SDK.
import { findTasksByDate, addTasks } from '@doist/todoist-mcp'
import { TodoistApi } from '@doist/todoist-sdk'
import { streamText } from 'ai'
// Create Todoist API client
const client = new TodoistApi(process.env.TODOIST_API_KEY)
// Helper to wrap tools with the client
function wrapTool(tool, todoistClient) {
return {
...tool,
execute(args) {
return tool.execute(args, todoistClient)
},
}
}
const result = streamText({
model: yourModel,
system: 'You are a helpful Todoist assistant',
tools: {
findTasksByDate: wrapTool(findTasksByDate, client),
addTasks: wrapTool(addTasks, client),
},
})
A key feature of this project is that tools can be reused, and are not written specifically for use in an MCP server. They can be hooked up as tools to other conversational AI interfaces (e.g. Vercel's AI SDK).
This project is in its early stages. Expect more and/or better tools soon.
Nevertheless, our goal is to provide a small set of tools that enable complete workflows, rather than just atomic actions, striking a balance between flexibility and efficiency for LLMs.
For our design philosophy, guidelines, and development patterns, see docs/tool-design.md.
For a complete list of available tools, see the src/tools directory.
This server includes search and fetch tools that follow the OpenAI MCP specification, enabling seamless integration with OpenAI's MCP protocol. These tools return JSON-encoded results optimized for OpenAI's requirements while maintaining compatibility with the broader MCP ecosystem.
See docs/mcp-server.md for full instructions on setting up the MCP server.
See docs/dev-setup.md for full setup instructions and CONTRIBUTING.md for contributor workflows and quality checks.
This project includes support for MCP Apps – interactive UI widgets rendered inline in AI chat interfaces. Widgets provide rich visual representations of tool outputs (e.g., task lists) instead of plain text.
See docs/mcp-apps.md for the widget architecture, build pipeline, and development workflow.
See CONTRIBUTING.md for:
scripts/run-tool.tsThis project uses release-please to automate version management and package publishing.
Make your changes using Conventional Commits:
feat: for new features (minor version bump)fix: for bug fixes (patch version bump)feat!: or fix!: for breaking changes (major version bump)docs: for documentation changeschore: for maintenance tasksci: for CI changesWhen commits are pushed to main:
After merging the release PR:
publish workflow is triggered