Claude Todo Emulator provides persistent task management with unique IDs, one in-progress task rule, and workspace-local
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
Time estimate: 15-60 minutes depending on server complexity
Prerequisites
Anytype
Transform any OpenAPI specification into callable tools. Easily test an API, handle authentication, and generate schemas
Linear
MCP server for Linear — enables Claude to interact with Linear data and workflows.
Telegram
Connect AI with Telegram using our telegram bot for efficient message monitoring, organizing, and handling via powerful
webclaw
Fast, local-first web content extraction for LLMs. Scrape, crawl, extract structured data — all from Rust. CLI, REST API
Google Sheets
Integrate with Google Sheets and Google Drive to manage spreadsheets easily using the Google Sheets API and advanced aut
Strong directory entry: Claude Todo Emulator surfaces stars and publisher context so we could sanity-check maintenance before adopting.
Claude Todo Emulator is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Claude Todo Emulator is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Claude Todo Emulator reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Claude Todo Emulator has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Useful MCP listing: Claude Todo Emulator is the kind of server we cite when onboarding engineers to host + tool permissions.
According to our notes, Claude Todo Emulator benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
We wired Claude Todo Emulator into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Claude Todo Emulator is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
I recommend Claude Todo Emulator for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
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Claude Desktop configuration
{
"mcpServers": {
"task-manager": {
"command": "uvx",
"args": [
"claude-todo-emulator"
]
}
}
}Adds persistent todo list functionality to AI coding assistants, replicating Claude Code's task management system with workspace-local storage.
Claude Todo Emulator is a community-built MCP server published by joehaddad2000 that provides AI assistants with tools and capabilities via the Model Context Protocol. Claude Todo Emulator provides persistent task management with unique IDs, one in-progress task rule, and workspace-local It is categorized under productivity. This server exposes 2 tools that AI clients can invoke during conversations and coding sessions.
You can install Claude Todo Emulator 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.
Add persistent task management to any AI coding assistant in Cursor, Windsurf, and other IDEs.
This MCP server replicates Claude Code's todo system, giving your AI assistant the ability to:
No installation required! Just add this to your MCP configuration:
Create .cursor/mcp.json in your project root:
{
"mcpServers": {
"task-manager": {
"command": "uvx",
"args": ["claude-todo-emulator"]
}
}
}
Create config.toml at your project root:
[mcp_servers.task-manager]
command = "uvx"
args = ["claude-todo-emulator"]
Add the JSON configuration above to your MCP settings file.
Restart your IDE and try: "Create a todo list for adding user authentication"
The system automatically downloads the package and sets up everything on first use!
Once configured, your AI assistant will automatically:
Create todos for complex tasks:
You: "Add dark mode support with user preferences"
AI: "I'll create a todo list for this multi-step feature:
- ✅ Add theme context and state management
- 🔄 Create dark mode CSS variables and styles
- ⏳ Build settings UI for theme switching
- ⏳ Add persistence to localStorage
- ⏳ Update existing components for theme support"
Track progress visually:
You: "What's the status on the authentication system?"
AI: "Current authentication tasks:
- ✅ Set up JWT middleware
- ✅ Create login/signup endpoints
- 🔄 Building user profile management (in progress)
- ⏳ Add password reset flow
- ⏳ Implement role-based permissions"
Maintain focus:
You: "Let's also add email notifications"
AI: "I'll add that to the todo list, but let me finish the current user profile task first to maintain focus."
TodoRead
{todos: Todo[]}TodoWrite
{todos: Todo[]}{success: boolean, count: number}Todo Schema
{
id: string;
content: string;
status: "pending" | "in_progress" | "completed";
priority: "high" | "medium" | "low";
created_at: string;
updated_at: string;
metadata?: object;
}
MIT License - see LICENSE file for details.
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.
Spec Workflow MCP
Structured spec-driven development workflow for AI-assisted software development. Creates detailed specifications before