Todoist MCP Server

MCP ServerFree

Create and manage Todoist tasks and projects via MCP.

Open Source

/ 100

12 capabilities

Capabilities12 decomposed

natural language task creation with semantic parameter parsing

Medium confidence

Translates conversational task descriptions into structured Todoist API calls by parsing natural language for task content, due dates (e.g., 'tomorrow', 'next Monday'), priority levels (1-4 semantic mapping), and optional descriptions. Uses date recognition to convert human-readable temporal references into ISO format and priority mapping to interpret semantic priority language, then submits via Todoist REST API with full parameter validation.

Solves for

Create a task from a natural language description without manually specifying due dates or priorityAdd a task with a due date using conversational phrasing like 'due tomorrow' or 'due next Friday'Set task priority using semantic language like 'high priority' or 'low priority' instead of numeric codes

Best for

Claude Desktop users managing tasks through conversational AI

Teams automating task creation from natural language prompts in AI workflows

Non-technical users who prefer speaking task requirements naturally rather than using structured forms

Requires

Todoist API token with write permissions

Node.js 16+ runtime

Claude Desktop with MCP server configured

Limitations

Date parsing relies on predefined natural language patterns; ambiguous dates (e.g., '3/4') may not resolve correctly

Priority mapping is fixed to Todoist's 1-4 scale; custom priority systems are not supported

No support for recurring task patterns or complex scheduling logic beyond single due dates

What makes it unique

Implements semantic date and priority parsing within the MCP tool handler itself, converting natural language directly to Todoist API parameters without requiring a separate NLP service or external date parsing library, reducing latency and external dependencies

vs alternatives

Faster than generic task creation APIs because date/priority parsing is embedded in the MCP handler rather than requiring round-trip calls to external NLP services or Claude for parameter extraction

filtered task retrieval with natural language query translation

Medium confidence

Queries Todoist tasks using natural language filters (e.g., 'overdue tasks', 'tasks due this week', 'high priority tasks') by translating conversational filter expressions into Todoist API filter syntax. Supports partial name matching for task identification, date range filtering, priority filtering, and result limiting. Implements filter translation logic that converts semantic language into Todoist's native query parameter format before executing REST API calls.

Solves for

Retrieve all overdue tasks without manually constructing API filter syntaxFind tasks due within a specific timeframe using natural language like 'due this week' or 'due in 3 days'Filter tasks by priority level or project using conversational languageSearch for a specific task by partial name match when the exact name is not remembered

Best for

Claude Desktop users querying their task list conversationally

AI agents that need to filter tasks before taking actions (e.g., completing overdue items)

Teams building task-aware workflows that require dynamic task filtering based on user input

Requires

Todoist API token with read permissions

Node.js 16+ runtime

Claude Desktop with MCP server configured

Limitations

Filter translation supports only predefined natural language patterns; complex boolean logic (AND/OR combinations) is not supported

Partial name matching is case-insensitive but does not support regex patterns or fuzzy matching

Date range filtering is limited to relative dates (today, this week, this month); absolute date ranges require manual API parameter specification

What makes it unique

Translates natural language filter expressions (e.g., 'overdue', 'this week') directly into Todoist API filter parameters within the MCP handler, avoiding the need for Claude to construct API syntax or make multiple round-trip calls to clarify filter intent

vs alternatives

More efficient than generic task APIs because filter translation is built into the MCP tool, reducing latency compared to systems that require Claude to generate filter syntax or make separate API calls to validate filter parameters

project and label management through todoist api

Medium confidence

Manages task organization by supporting project assignment and label association through Todoist API integration. Enables users to specify project_id when creating or updating tasks, and supports label assignment through task parameters. Implements project and label lookups to translate project/label names into IDs required by Todoist API, supporting task organization without requiring users to know numeric project IDs.

Solves for

Assign tasks to specific projects using project names or IDsAdd labels to tasks for categorization and filteringOrganize tasks across multiple projects through conversational commandsLook up project and label IDs from names for API submission

Best for

Claude Desktop users organizing tasks across multiple projects

Teams using Todoist projects for workflow organization

Workflows where task categorization and labeling are important

Requires

Todoist API token with read/write permissions

Node.js 16+ runtime

Existing projects and labels in Todoist workspace

Limitations

Project lookup requires a separate API call to fetch project list; no caching is implemented

Label management is limited to assignment; label creation is not supported through this tool

No support for nested projects or project hierarchies

What makes it unique

Integrates project and label management into task creation/update tools, allowing users to organize tasks by project and label without separate API calls, reducing friction in conversational task management

vs alternatives

More convenient than direct API project assignment because it supports project name lookup in addition to IDs, making it suitable for conversational interfaces where users reference projects by name

executable cli binary with npm package distribution

Medium confidence

Packages the Todoist MCP server as an executable CLI binary (todoist-mcp-server) distributed via npm, enabling one-command installation and execution. Implements build process using TypeScript compilation (tsc) with executable permissions set via shx chmod +x, generating dist/index.js as the main entry point. Supports installation via npm install or Smithery package manager, with automatic binary availability in PATH after installation.

Solves for

Install Todoist MCP server with a single npm commandRun the MCP server as a CLI executable without manual configurationDistribute the MCP server to users via npm package registryEnable automatic updates through npm package management

Best for

Claude Desktop users installing MCP servers via npm

Developers distributing MCP servers to the community

Teams deploying MCP servers with standard npm tooling

Requires

Node.js 16+ with npm

npm account for package publishing (for maintainers)

TypeScript 4.5+ for build process

Limitations

Requires Node.js and npm to be installed on the user's system

Binary is platform-specific; separate builds may be needed for Windows, macOS, and Linux

No automatic updates; users must manually run npm update to get new versions

What makes it unique

Distributes MCP server as an npm package with executable binary, enabling one-command installation and integration with Claude Desktop without manual configuration or build steps

vs alternatives

More accessible than manual installation because users can install with npm install @smithery/todoist-mcp-server, reducing setup friction compared to cloning repositories and building from source

task attribute modification with name-based task identification

Medium confidence

Updates task attributes (name, description, due date, priority, project) by first identifying the target task using partial name matching against the task list, then applying the requested modifications via Todoist REST API. Implements a two-step process: (1) search for task by name fragment, (2) update matched task with new attribute values. Supports atomic updates of individual attributes without requiring full task replacement.

Solves for

Rename a task using a partial description when the exact name is not knownChange a task's due date or priority after creationMove a task to a different project without recreating itUpdate task description or add additional context to an existing task

Best for

Claude Desktop users modifying tasks conversationally without navigating the Todoist UI

AI agents that need to adjust task properties based on dynamic conditions or user feedback

Workflows where task metadata (due date, priority) changes frequently and requires programmatic updates

Requires

Todoist API token with write permissions

Node.js 16+ runtime

Claude Desktop with MCP server configured

Limitations

Task identification relies on partial name matching; tasks with very similar names may cause ambiguous matches

Updates are applied to the first matching task; if multiple tasks match the name fragment, only the first is updated

No support for conditional updates (e.g., 'update only if priority is currently low')

What makes it unique

Implements client-side task identification via partial name matching before API update, allowing users to reference tasks by incomplete descriptions without requiring exact task IDs, reducing friction in conversational workflows

vs alternatives

More user-friendly than direct API updates because it accepts partial task names instead of requiring task IDs, making it suitable for conversational interfaces where users describe tasks naturally rather than providing identifiers

task completion with partial name matching and status confirmation

Medium confidence

Marks tasks as complete by identifying the target task using partial name matching, then submitting a completion request to the Todoist API. Implements name-based task lookup followed by a completion API call, with optional status confirmation returned to the user. Supports completing tasks without requiring exact task IDs or manual task selection.

Solves for

Mark a task as done using a partial description without navigating the Todoist UIComplete multiple tasks in sequence by referencing them conversationallyConfirm task completion status after marking a task as done

Best for

Claude Desktop users completing tasks through conversational commands

AI agents managing task workflows and marking items as done based on external triggers

Teams using Claude as a task management interface for quick task completion

Requires

Todoist API token with write permissions

Node.js 16+ runtime

Claude Desktop with MCP server configured

Limitations

Partial name matching may match unintended tasks if multiple tasks have similar names

Completion is irreversible through this tool; no undo capability is provided

Status confirmation is returned but does not include task history or completion timestamp details

What makes it unique

Combines task identification (partial name matching) with completion in a single MCP tool call, eliminating the need for separate lookup and completion steps, reducing round-trips in conversational task management workflows

vs alternatives

More efficient than generic task completion APIs because it integrates name-based task lookup, reducing the number of API calls and user interactions required to complete a task from a conversational description

task deletion with name-based identification and deletion confirmation

Medium confidence

Removes tasks from Todoist by identifying the target task using partial name matching, then submitting a deletion request to the Todoist API. Implements name-based task lookup followed by a delete API call, with confirmation returned to the user. Supports task removal without requiring exact task IDs, making deletion accessible through conversational interfaces.

Solves for

Delete a task using a partial description without manually finding its IDRemove unwanted tasks from Todoist through conversational commandsConfirm task deletion after removal

Best for

Claude Desktop users removing tasks conversationally

AI agents cleaning up completed or obsolete tasks from task lists

Workflows where task cleanup is automated based on external conditions

Requires

Todoist API token with write permissions

Node.js 16+ runtime

Claude Desktop with MCP server configured

Limitations

Deletion is permanent; no recovery mechanism is provided by this tool

Partial name matching may delete unintended tasks if multiple tasks have similar names

Deletion confirmation does not include pre-deletion task details or recovery options

What makes it unique

Integrates name-based task identification with deletion in a single MCP tool call, allowing users to delete tasks by conversational description rather than task ID, reducing friction in task cleanup workflows

vs alternatives

More accessible than direct API deletion because it accepts partial task names instead of requiring task IDs, making it suitable for conversational interfaces where users describe tasks naturally

mcp protocol bridging with stdio transport and schema-based tool registration

Medium confidence

Implements the Model Context Protocol (MCP) server using stdio transport to enable bidirectional communication between Claude Desktop and the Todoist MCP server. Uses schema-based tool registration (CallToolRequestSchema) to define and validate tool parameters, with StdioServerTransport handling message serialization and deserialization. Implements the MCP server lifecycle (initialization, tool discovery, request handling) with proper error handling and type safety through TypeScript.

Solves for

Enable Claude Desktop to discover and invoke Todoist task management toolsEstablish a persistent connection between Claude and the Todoist MCP serverValidate tool parameters against defined schemas before executionHandle MCP protocol messages and route them to appropriate tool handlers

Best for

Claude Desktop users integrating Todoist task management into their AI workflow

Developers building MCP servers that need to bridge Claude with external APIs

Teams deploying MCP servers for local AI-powered task automation

Requires

Node.js 16+ runtime

Claude Desktop 0.1.0+ with MCP support

Todoist API token configured in MCP server environment

Limitations

Stdio transport is synchronous; concurrent requests are queued and processed sequentially

MCP server must be running as a separate process; no in-process integration with Claude

Schema validation is performed at the MCP layer; complex validation logic must be implemented in tool handlers

What makes it unique

Implements MCP server with stdio transport and schema-based tool registration, providing a lightweight protocol bridge that requires no external dependencies beyond Node.js and the Todoist API, enabling direct Claude-to-Todoist integration without cloud intermediaries

vs alternatives

More lightweight than REST API wrappers because it uses stdio transport (no HTTP overhead) and integrates directly with Claude's MCP protocol, reducing latency and eliminating the need for separate API gateway infrastructure

type-safe parameter validation with typescript schema enforcement

Medium confidence

Enforces type safety and parameter validation across all MCP tools using TypeScript type definitions and schema validation. Implements CallToolRequestSchema to define expected parameters for each tool (content, due_date, priority, project_id, etc.), with runtime validation before tool execution. Validates input types, required fields, and parameter ranges (e.g., priority 1-4) to prevent invalid API calls to Todoist.

Solves for

Prevent invalid parameters from being sent to Todoist APIProvide clear error messages when tool parameters are malformedEnsure type safety across the MCP tool interfaceValidate priority levels, dates, and other constrained parameters before API submission

Best for

Developers building MCP servers that require strict parameter validation

Teams deploying MCP servers in production where invalid API calls must be prevented

Systems where clear error messages are critical for debugging Claude-generated tool calls

Requires

TypeScript 4.5+ for type definitions

Node.js 16+ runtime

MCP schema validation library (included in MCP SDK)

Limitations

Schema validation is limited to type checking and basic constraints; complex business logic validation must be implemented in tool handlers

Error messages are generated at the schema level; detailed validation context is not always available

Schema definitions are static; dynamic schema generation based on Todoist API responses is not supported

What makes it unique

Implements schema-based parameter validation at the MCP protocol layer using TypeScript type definitions, catching invalid parameters before they reach the Todoist API and preventing malformed requests from being submitted

vs alternatives

More robust than runtime-only validation because it combines TypeScript compile-time type checking with MCP schema validation, catching errors at multiple layers and providing clear error messages to Claude

todoist rest api integration with authentication and error handling

Medium confidence

Integrates with Todoist's REST API by managing authentication (API token in Authorization header), constructing API requests for each tool operation, and handling API responses and errors. Implements HTTP client logic to submit requests to Todoist endpoints (create task, get tasks, update task, complete task, delete task) with proper error handling for rate limits, authentication failures, and invalid requests. Translates Todoist API responses into MCP tool results.

Solves for

Authenticate with Todoist API using a stored API tokenSubmit task management requests to Todoist REST API endpointsHandle API errors and rate limiting gracefullyTranslate Todoist API responses into MCP tool results

Best for

MCP server developers integrating with Todoist

Teams deploying Todoist automation that requires reliable API integration

Systems where API error handling and retry logic are critical

Requires

Todoist API token (generated in Todoist account settings)

Node.js 16+ with built-in fetch API or node-fetch library

Network connectivity to Todoist API (api.todoist.com)

Limitations

Authentication relies on a single API token; no support for OAuth or token refresh

Rate limiting is handled passively (errors are returned to Claude); no built-in retry logic with exponential backoff

API error messages from Todoist are passed through without translation; users must understand Todoist error codes

What makes it unique

Implements Todoist API integration directly in the MCP server without external HTTP client libraries, using Node.js built-in fetch API to minimize dependencies and reduce deployment complexity

vs alternatives

Simpler than wrapper libraries because it implements API calls directly in the MCP handler, reducing external dependencies and making it easier to customize error handling and request formatting for MCP-specific requirements

date parsing and normalization for natural language temporal references

Medium confidence

Converts natural language date expressions (e.g., 'tomorrow', 'next Monday', 'this week', 'in 3 days') into ISO 8601 format required by Todoist API. Implements pattern matching for common temporal phrases and calculates relative dates based on the current date. Supports both relative dates (today, tomorrow, next week) and absolute references (specific day names), normalizing all inputs to ISO format before API submission.

Solves for

Accept natural language due dates in task creation and updatesConvert 'tomorrow', 'next Monday', 'this week' into ISO date formatSupport relative date calculations (e.g., 'in 3 days')Normalize dates for Todoist API without requiring users to format dates manually

Best for

Claude Desktop users creating tasks with natural language due dates

Conversational task management interfaces where users describe dates naturally

Workflows where date parsing must happen without external date libraries

Requires

Node.js 16+ with native Date object support

Current date/time available on the server

Limitations

Date parsing supports only predefined patterns; ambiguous dates (e.g., '3/4') may not resolve correctly

No support for complex date expressions (e.g., 'every other Tuesday', 'last day of the month')

Timezone handling is not implemented; all dates are assumed to be in the user's local timezone

What makes it unique

Implements date parsing directly in the MCP tool handler using pattern matching and relative date calculations, avoiding external date libraries and enabling lightweight date normalization without additional dependencies

vs alternatives

More efficient than calling Claude for date parsing because date conversion is handled locally in the MCP handler, reducing round-trips and latency for common temporal expressions

priority level semantic mapping and translation

Medium confidence

Translates semantic priority language (e.g., 'high', 'low', 'urgent', 'normal') into Todoist's numeric priority scale (1-4, where 4 is highest). Implements a mapping table that converts natural language priority expressions into the corresponding numeric values required by Todoist API. Supports both explicit numeric priorities and semantic language, normalizing all inputs to Todoist's numeric format.

Solves for

Accept priority descriptions in natural language (e.g., 'high priority', 'low priority')Map semantic priority language to Todoist's 1-4 numeric scaleSupport both numeric and semantic priority specifications in task creation and updatesNormalize priority values for Todoist API without requiring users to know numeric codes

Best for

Claude Desktop users setting task priorities using natural language

Conversational task management where users describe priorities semantically

Workflows where priority mapping must be consistent across multiple tools

Requires

Node.js 16+ runtime

Limitations

Priority mapping is fixed to Todoist's 1-4 scale; custom priority systems are not supported

No support for relative priority adjustments (e.g., 'increase priority by one level')

Semantic mapping is limited to predefined terms; custom priority language is not supported

What makes it unique

Implements priority mapping as a simple lookup table in the MCP tool handler, enabling semantic priority language without external NLP services or Claude round-trips, reducing latency and dependencies

vs alternatives

More efficient than asking Claude to translate priority language because mapping is handled locally in the MCP handler, reducing round-trips and ensuring consistent priority mapping across all tool invocations

Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.

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Best For

✓Claude Desktop users managing tasks through conversational AI
✓Teams automating task creation from natural language prompts in AI workflows
✓Non-technical users who prefer speaking task requirements naturally rather than using structured forms
✓Claude Desktop users querying their task list conversationally
✓AI agents that need to filter tasks before taking actions (e.g., completing overdue items)
✓Teams building task-aware workflows that require dynamic task filtering based on user input
✓Claude Desktop users organizing tasks across multiple projects
✓Teams using Todoist projects for workflow organization

Known Limitations

⚠Date parsing relies on predefined natural language patterns; ambiguous dates (e.g., '3/4') may not resolve correctly
⚠Priority mapping is fixed to Todoist's 1-4 scale; custom priority systems are not supported
⚠No support for recurring task patterns or complex scheduling logic beyond single due dates
⚠Task creation is synchronous; bulk creation of 100+ tasks may experience latency
⚠Filter translation supports only predefined natural language patterns; complex boolean logic (AND/OR combinations) is not supported
⚠Partial name matching is case-insensitive but does not support regex patterns or fuzzy matching

Requirements

Todoist API token with write permissionsNode.js 16+ runtimeClaude Desktop with MCP server configuredValid Todoist project ID or default project configuredTodoist API token with read permissionsValid Todoist workspace with existing tasksTodoist API token with read/write permissionsExisting projects and labels in Todoist workspace

Input / Output

Accepts: text (natural language task description), structured JSON (optional: explicit due_date, priority, project_id), text (natural language filter query, e.g., 'overdue tasks', 'high priority'), structured JSON (optional: explicit filter parameters, limit, offset), text (project name or ID), text array (label names), structured JSON (project_id, labels), npm install command, CLI arguments (environment variables for API token), text (task name fragment for identification), structured JSON (new attribute values: name, description, due_date, priority, project_id), MCP protocol messages (JSON-RPC format), tool invocation requests with parameters, structured JSON (tool parameters), HTTP headers (Authorization token), text (natural language date expression, e.g., 'tomorrow', 'next Friday'), text (semantic priority: 'high', 'low', 'urgent', 'normal'), numeric priority (1-4)

Produces: structured JSON (task object with id, content, due_date, priority, project_id), error response with validation details, structured JSON array (task objects with id, content, due_date, priority, project_id, completed status), empty array if no tasks match filters, error response with filter parsing details, structured JSON (task object with project_id and labels), error if project/label not found, Executable binary in node_modules/.bin/todoist-mcp-server, MCP server process listening on stdio, structured JSON (updated task object with modified attributes), error response if task not found or update fails, structured JSON (confirmation object with task id, completion status, timestamp), error response if task not found or completion fails, structured JSON (confirmation object with deleted task id, deletion status), error response if task not found or deletion fails, MCP protocol responses (JSON-RPC format), tool execution results or error messages, validation success (parameters passed to tool handler), validation error with details on invalid parameters, structured JSON (Todoist API response data), error response with HTTP status and Todoist error details, ISO 8601 date string (e.g., '2025-05-25'), error if date expression cannot be parsed, numeric priority (1-4) for Todoist API, error if priority value is invalid

UnfragileRank

Adoption70%(30% weight)

Quality23%(25% weight)

Ecosystem52%(25% weight)

Match Graph10%(15% weight)

Freshness100%(5% weight)

UnfragileRank is computed from adoption signals, documentation quality, ecosystem connectivity, match graph feedback, and freshness. No artifact can pay for a higher rank.

Type: MCP Server

12 capabilities

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Community MCP server for Todoist task management. Provides tools to create, update, complete, and delete tasks, manage projects and labels, and query tasks by filters and due dates.

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Capabilities12 decomposed

natural language task creation with semantic parameter parsing

Medium confidence

Solves for

Best for

Claude Desktop users managing tasks through conversational AI

Teams automating task creation from natural language prompts in AI workflows

Non-technical users who prefer speaking task requirements naturally rather than using structured forms

Requires

Todoist API token with write permissions

Node.js 16+ runtime

Claude Desktop with MCP server configured

Limitations

Date parsing relies on predefined natural language patterns; ambiguous dates (e.g., '3/4') may not resolve correctly

Priority mapping is fixed to Todoist's 1-4 scale; custom priority systems are not supported

No support for recurring task patterns or complex scheduling logic beyond single due dates

What makes it unique

vs alternatives

Faster than generic task creation APIs because date/priority parsing is embedded in the MCP handler rather than requiring round-trip calls to external NLP services or Claude for parameter extraction

filtered task retrieval with natural language query translation

Medium confidence

Solves for

Best for

Claude Desktop users querying their task list conversationally

AI agents that need to filter tasks before taking actions (e.g., completing overdue items)

Teams building task-aware workflows that require dynamic task filtering based on user input

Requires

Todoist API token with read permissions

Node.js 16+ runtime

Claude Desktop with MCP server configured

Limitations

Filter translation supports only predefined natural language patterns; complex boolean logic (AND/OR combinations) is not supported

Partial name matching is case-insensitive but does not support regex patterns or fuzzy matching

Date range filtering is limited to relative dates (today, this week, this month); absolute date ranges require manual API parameter specification

What makes it unique

vs alternatives

project and label management through todoist api

Medium confidence

Solves for

Best for

Claude Desktop users organizing tasks across multiple projects

Teams using Todoist projects for workflow organization

Workflows where task categorization and labeling are important

Requires

Todoist API token with read/write permissions

Node.js 16+ runtime

Existing projects and labels in Todoist workspace

Limitations

Project lookup requires a separate API call to fetch project list; no caching is implemented

Label management is limited to assignment; label creation is not supported through this tool

No support for nested projects or project hierarchies

What makes it unique

vs alternatives

More convenient than direct API project assignment because it supports project name lookup in addition to IDs, making it suitable for conversational interfaces where users reference projects by name

executable cli binary with npm package distribution

Medium confidence

Solves for

Best for

Claude Desktop users installing MCP servers via npm

Developers distributing MCP servers to the community

Teams deploying MCP servers with standard npm tooling

Requires

Node.js 16+ with npm

npm account for package publishing (for maintainers)

TypeScript 4.5+ for build process

Limitations

Requires Node.js and npm to be installed on the user's system

Binary is platform-specific; separate builds may be needed for Windows, macOS, and Linux

No automatic updates; users must manually run npm update to get new versions

What makes it unique

Distributes MCP server as an npm package with executable binary, enabling one-command installation and integration with Claude Desktop without manual configuration or build steps

vs alternatives

More accessible than manual installation because users can install with npm install @smithery/todoist-mcp-server, reducing setup friction compared to cloning repositories and building from source

task attribute modification with name-based task identification

Medium confidence

Solves for

Best for

Claude Desktop users modifying tasks conversationally without navigating the Todoist UI

AI agents that need to adjust task properties based on dynamic conditions or user feedback

Workflows where task metadata (due date, priority) changes frequently and requires programmatic updates

Requires

Todoist API token with write permissions

Node.js 16+ runtime

Claude Desktop with MCP server configured

Limitations

Task identification relies on partial name matching; tasks with very similar names may cause ambiguous matches

Updates are applied to the first matching task; if multiple tasks match the name fragment, only the first is updated

No support for conditional updates (e.g., 'update only if priority is currently low')

What makes it unique

vs alternatives

task completion with partial name matching and status confirmation

Medium confidence

Solves for

Best for

Claude Desktop users completing tasks through conversational commands

AI agents managing task workflows and marking items as done based on external triggers

Teams using Claude as a task management interface for quick task completion

Requires

Todoist API token with write permissions

Node.js 16+ runtime

Claude Desktop with MCP server configured

Limitations

Partial name matching may match unintended tasks if multiple tasks have similar names

Completion is irreversible through this tool; no undo capability is provided

Status confirmation is returned but does not include task history or completion timestamp details

What makes it unique

vs alternatives

task deletion with name-based identification and deletion confirmation

Medium confidence

Solves for

Delete a task using a partial description without manually finding its IDRemove unwanted tasks from Todoist through conversational commandsConfirm task deletion after removal

Best for

Claude Desktop users removing tasks conversationally

AI agents cleaning up completed or obsolete tasks from task lists

Workflows where task cleanup is automated based on external conditions

Requires

Todoist API token with write permissions

Node.js 16+ runtime

Claude Desktop with MCP server configured

Limitations

Deletion is permanent; no recovery mechanism is provided by this tool

Partial name matching may delete unintended tasks if multiple tasks have similar names

Deletion confirmation does not include pre-deletion task details or recovery options

What makes it unique

vs alternatives

More accessible than direct API deletion because it accepts partial task names instead of requiring task IDs, making it suitable for conversational interfaces where users describe tasks naturally

mcp protocol bridging with stdio transport and schema-based tool registration

Medium confidence

Solves for

Best for

Claude Desktop users integrating Todoist task management into their AI workflow

Developers building MCP servers that need to bridge Claude with external APIs

Teams deploying MCP servers for local AI-powered task automation

Requires

Node.js 16+ runtime

Claude Desktop 0.1.0+ with MCP support

Todoist API token configured in MCP server environment

Limitations

Stdio transport is synchronous; concurrent requests are queued and processed sequentially

MCP server must be running as a separate process; no in-process integration with Claude

Schema validation is performed at the MCP layer; complex validation logic must be implemented in tool handlers

What makes it unique

vs alternatives

type-safe parameter validation with typescript schema enforcement

Medium confidence

Solves for

Best for

Developers building MCP servers that require strict parameter validation

Teams deploying MCP servers in production where invalid API calls must be prevented

Systems where clear error messages are critical for debugging Claude-generated tool calls

Requires

TypeScript 4.5+ for type definitions

Node.js 16+ runtime

MCP schema validation library (included in MCP SDK)

Limitations

Schema validation is limited to type checking and basic constraints; complex business logic validation must be implemented in tool handlers

Error messages are generated at the schema level; detailed validation context is not always available

Schema definitions are static; dynamic schema generation based on Todoist API responses is not supported

What makes it unique

vs alternatives

todoist rest api integration with authentication and error handling

Medium confidence

Solves for

Best for

MCP server developers integrating with Todoist

Teams deploying Todoist automation that requires reliable API integration

Systems where API error handling and retry logic are critical

Requires

Todoist API token (generated in Todoist account settings)

Node.js 16+ with built-in fetch API or node-fetch library

Network connectivity to Todoist API (api.todoist.com)

Limitations

Authentication relies on a single API token; no support for OAuth or token refresh

Rate limiting is handled passively (errors are returned to Claude); no built-in retry logic with exponential backoff

API error messages from Todoist are passed through without translation; users must understand Todoist error codes

What makes it unique

Implements Todoist API integration directly in the MCP server without external HTTP client libraries, using Node.js built-in fetch API to minimize dependencies and reduce deployment complexity

vs alternatives

date parsing and normalization for natural language temporal references

Medium confidence

Solves for

Best for

Claude Desktop users creating tasks with natural language due dates

Conversational task management interfaces where users describe dates naturally

Workflows where date parsing must happen without external date libraries

Requires

Node.js 16+ with native Date object support

Current date/time available on the server

Limitations

Date parsing supports only predefined patterns; ambiguous dates (e.g., '3/4') may not resolve correctly

No support for complex date expressions (e.g., 'every other Tuesday', 'last day of the month')

Timezone handling is not implemented; all dates are assumed to be in the user's local timezone

What makes it unique

vs alternatives

More efficient than calling Claude for date parsing because date conversion is handled locally in the MCP handler, reducing round-trips and latency for common temporal expressions

priority level semantic mapping and translation

Medium confidence

Solves for

Best for

Claude Desktop users setting task priorities using natural language

Conversational task management where users describe priorities semantically

Workflows where priority mapping must be consistent across multiple tools

Requires

Node.js 16+ runtime

Limitations

Priority mapping is fixed to Todoist's 1-4 scale; custom priority systems are not supported

No support for relative priority adjustments (e.g., 'increase priority by one level')

Semantic mapping is limited to predefined terms; custom priority language is not supported

What makes it unique

vs alternatives

Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.

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Todoist MCP Server

Capabilities12 decomposed

natural language task creation with semantic parameter parsing

filtered task retrieval with natural language query translation

project and label management through todoist api

executable cli binary with npm package distribution

task attribute modification with name-based task identification

task completion with partial name matching and status confirmation

task deletion with name-based identification and deletion confirmation

mcp protocol bridging with stdio transport and schema-based tool registration

type-safe parameter validation with typescript schema enforcement

todoist rest api integration with authentication and error handling

date parsing and normalization for natural language temporal references

priority level semantic mapping and translation

Related Artifactssharing capabilities

Todo.is

Bottr

Taskade

Assisterr

Jife

Antispace

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

About

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Alternatives to Todoist MCP Server

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Data Sources

Todoist MCP Server

Capabilities12 decomposed

natural language task creation with semantic parameter parsing

filtered task retrieval with natural language query translation

project and label management through todoist api

executable cli binary with npm package distribution

task attribute modification with name-based task identification

task completion with partial name matching and status confirmation

task deletion with name-based identification and deletion confirmation

mcp protocol bridging with stdio transport and schema-based tool registration

type-safe parameter validation with typescript schema enforcement

todoist rest api integration with authentication and error handling

date parsing and normalization for natural language temporal references

priority level semantic mapping and translation

Related Artifactssharing capabilities

Todo.is

Bottr

Taskade

Assisterr

Jife

Antispace

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

About

Categories

Alternatives to Todoist MCP Server

Are you the builder of Todoist MCP Server?

Get the weekly brief

Data Sources