agent-todo-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@agent-todo-mcplist all todos in my-react-app project"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Agent TODO MCP Server
Now all editors have this feature so yep...
A Model Context Protocol server for AI agents to manage tasks and track progress across projects.
Features
Create, update, and manage TODOs with detailed metadata
Track progress, status, priority, and dependencies
Explicit project isolation to prevent data mixup between workspaces
Search, filter, and generate comprehensive reports
Persistent JSON storage with complete project separation
Related MCP server: Tiny TODO MCP
Installation
Via npm (Recommended)
npm install -g agent-todo-mcpFrom Source
git clone https://github.com/w04m1/agent-todo-mcp.git
cd agent-todo-mcp
npm install
npm run build
npm install -g .Configuration
Add to your Claude Desktop/Cursor/VSCode/etc. config:
{
"mcpServers": {
"agent-todo": {
"command": "agent-todo-mcp"
}
}
}How AI Models Use This Server
When AI models interact with this MCP server, they follow this workflow:
Check existing projects with
list_projectsCreate or switch to a project with
switch_projectCreate and manage TODOs within that project workspace
Project Management
Project Naming Best Practices
When creating projects, use descriptive names that clearly identify the workspace:
✅
"my-react-app"- Good descriptive name✅
"backend-api-v2"- Clear project identifier✅
"research-ml-models"- Descriptive and specific❌
"project1"- Too generic❌
"temp"- Not descriptive
Project Isolation & Storage
Each project workspace is completely isolated. TODOs are stored in:
~/.agent-todos/
├── my-react-app/todos.json # Project: "my-react-app"
├── backend-api-v2/todos.json # Project: "backend-api-v2"
├── research-ml-models/todos.json # Project: "research-ml-models"
└── default-workspace/todos.json # Default fallback projectArchitecture
Complete Isolation: Each project has its own TODO storage
Explicit Management: Projects are created explicitly via
switch_projecttoolPersistent Storage: All data persists in
~/.agent-todos/{projectId}/⚠️ No Deletion: Projects cannot be deleted through the API (only individual TODOs can be deleted)
Available Tools
Project Management
list_projects- List all available project workspacesswitch_project- Create new project or switch between existing onesget_project_info- Show current project details
Core Management
create_todo- Create new tasksupdate_todo- Update existing tasksdelete_todo- Remove taskslist_todos- List and filter tasksget_todo- Get detailed task info
Search & Analytics
search_todos- Search across all tasksgenerate_report- Create progress reportsget_stats- Quick statistics
TODO Structure
interface Todo {
id: string;
title: string;
description?: string;
status: "pending" | "in-progress" | "completed" | "blocked";
priority: "low" | "medium" | "high" | "urgent";
progress: number; // 0-100
tags: string[];
dependencies: string[]; // Other TODO IDs
dueDate?: string;
metadata: Record<string, any>;
createdAt: string;
updatedAt: string;
}Development
npm run dev # Development mode
npm run build # Build project
npm start # Run built serverLicense
MIT
Built with AI for AI 🤡
Maintenance
Resources
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Looking for Admin?
If you are the server author, to access and configure the admin panel.
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