didatodolist-mcp — security grade SAFE, quality 71/100

Security audit verdict: SAFE · quality 71/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by GalaxyXieyu · MCP Server · ★ 84

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

🔒 Is didatodolist-mcp safe to install? View the security audit →

About didatodolist-mcp

TickTick MCP Service Bring TickTick task and goal data into MCP workflows with official OAuth and Open API support. Case study · AgentsGalaxy · GitHub connects TickTick (Dida365) data to MCP-friendly workflows, with goal management, task analytics, and automation-friendly interfaces built on top of the official auth and API surface. Why it matters official OAuth 2.0 and Open API support makes the integration easier to trust MCP packaging makes task data more useful inside AI-native workflows the repo is suitable for productivity tooling, research flows, and personal operating systems Quick Start Clone the repo and install Python dependencies. Configure with your client credentials. Run the OAuth helper once to get access and refresh tokens. Start the MCP service and connect it to your editor or automation runtime.

dida365mcpoauthproductivitypythontask-managementticktick

Quick Facts

Stars84
Forks11
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score70.8132398655211/100
Open Issues2
Last Updated2026-04-19
Created2025-04-26
Platformsmcp, python
Est. Tokens~35k

Compatible Skills

These tools work well together with didatodolist-mcp for enhanced workflows:

  • pydantic-ai-todo — semantic(0.21)+complementary+rare_topics+same_lang+similar_pop+shared_platform (57%)
  • gen-mentor — semantic(0.16)+complementary+same_lang+similar_pop+shared_platform (50%)
  • AI-company — semantic(0.17)+rare_topics+same_lang+similar_pop+shared_platform (46%)

didatodolist-mcp alternative? Top 6 similar tools

Looking for a didatodolist-mcp alternative? If you're comparing didatodolist-mcp with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

  • taskdog by Kohei-Wada · ⭐ 358

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    Model Context Protocol server for Vikunja task management. Enables AI assistants to interact with Vikunja inst

  • clickup-mcp-server by taazkareem · ⭐ 52

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  • daymon by daymonio · ⭐ 365

    Daymon puts your favorite AI to work 24/7. It schedules, remembers, and orchestrates your own virtual team. Fr

  • OmniFocus-MCP by themotionmachine · ⭐ 244

    Let LLMs interface with your tasks and projects through the Model Context Protocol. Add, organize, and query y

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Frequently Asked Questions

What is didatodolist-mcp?

didatodolist-mcp is Bring TickTick task and goal data into MCP workflows with official OAuth and Open API support.. It is categorized as a MCP Server with 84 GitHub stars.

What programming language is didatodolist-mcp written in?

didatodolist-mcp is primarily written in Python. It covers topics such as dida365, mcp, oauth.

How do I install or use didatodolist-mcp?

You can find installation instructions and usage details in the didatodolist-mcp GitHub repository at github.com/GalaxyXieyu/didatodolist-mcp. The project has 84 stars and 11 forks, indicating an active community.

What license does didatodolist-mcp use?

didatodolist-mcp is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to didatodolist-mcp?

The top alternatives to didatodolist-mcp on Agent Skills Hub include taskdog, vikunja-mcp, clickup-mcp-server. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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