by liorfranko
Organize projects using leading project track software. Convert tasks with dependency tracking for optimal time manageme
Converts natural language task descriptions into organized development plans with dependency tracking, step-by-step implementation guides, and verification criteria.
Chain of Thought Task Manager is a community-built MCP server published by liorfranko that provides AI assistants with tools and capabilities via the Model Context Protocol. Organize projects using leading project track software. Convert tasks with dependency tracking for optimal time manageme It is categorized under productivity.
You can install Chain of Thought Task Manager 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
Chain of Thought Task Manager 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
Chain of Thought Task Manager is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
We wired Chain of Thought Task Manager into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Strong directory entry: Chain of Thought Task Manager surfaces stars and publisher context so we could sanity-check maintenance before adopting.
Useful MCP listing: Chain of Thought Task Manager is the kind of server we cite when onboarding engineers to host + tool permissions.
Chain of Thought Task Manager reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Chain of Thought Task Manager is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
According to our notes, Chain of Thought Task Manager benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Chain of Thought Task Manager has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Chain of Thought Task Manager reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
We evaluated Chain of Thought Task Manager against two servers with overlapping tools; this profile had the clearer scope statement.
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<a href="https://glama.ai/mcp/servers/@liorfranko/mcp-chain-of-thought"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@liorfranko/mcp-chain-of-thought/badge" /> </a>🚀 An intelligent task management system based on Model Context Protocol (MCP), providing an efficient programming workflow framework for AI Agents.
ENABLE_GUI=true)ENABLE_DETAILED_MODE=true)process_thought toolnpx -y @smithery/cli install @liorfranko/mcp-chain-of-thought --client claude
npm install
npm run build
Add to your Cursor configuration file (~/.cursor/mcp.json or project-specific .cursor/mcp.json):
{
"mcpServers": {
"chain-of-thought": {
"command": "npx",
"args": ["-y", "mcp-chain-of-thought"],
"env": {
"DATA_DIR": "/path/to/project/data", // Must use absolute path
"ENABLE_THOUGHT_CHAIN": "true",
"TEMPLATES_USE": "en",
"ENABLE_GUI": "true",
"ENABLE_DETAILED_MODE": "true"
}
}
}
}
⚠️ Important:
DATA_DIRmust use an absolute path.
| Category | Tool | Description |
|---|---|---|
| 📋 Planning | plan_task | Start planning tasks |
analyze_task | Analyze requirements | |
process_thought | Step-by-step reasoning | |
reflect_task | Improve solution concepts | |
init_project_rules | Set project standards | |
| 🧩 Management | split_tasks | Break into subtasks |
list_tasks | Show all tasks | |
query_task | Search tasks | |
get_task_detail | Show task details | |
delete_task | Remove tasks | |
| ▶️ Execution | execute_task | Run specific tasks |
verify_task | Verify completion | |
complete_task | Mark as completed |
This project is licensed under the MIT License - see the LICENSE file for details.
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.