by kazuph
TaskManager streamlines project tracking and time management with efficient task queues, ideal for managing projects sof
Manages tasks in a queue-based system where you can plan task lists, execute them one by one, and track completion status with unique IDs.
TaskManager is a community-built MCP server published by kazuph that provides AI assistants with tools and capabilities via the Model Context Protocol. TaskManager streamlines project tracking and time management with efficient task queues, ideal for managing projects sof It is categorized under productivity. This server exposes 10 tools that AI clients can invoke during conversations and coding sessions.
You can install TaskManager 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
TaskManager 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
We evaluated TaskManager against two servers with overlapping tools; this profile had the clearer scope statement.
We wired TaskManager into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Useful MCP listing: TaskManager is the kind of server we cite when onboarding engineers to host + tool permissions.
We evaluated TaskManager against two servers with overlapping tools; this profile had the clearer scope statement.
I recommend TaskManager for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
TaskManager has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
TaskManager has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Strong directory entry: TaskManager surfaces stars and publisher context so we could sanity-check maintenance before adopting.
TaskManager reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
TaskManager is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
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Model Context Protocol server for Task Management. This allows Claude Desktop (or any MCP client) to manage and execute tasks in a queue-based system.
<a href="https://glama.ai/mcp/servers/bdjh7kx05h"><img width="380" height="200" src="https://glama.ai/mcp/servers/bdjh7kx05h/badge" alt="@kazuph/mcp-taskmanager MCP server" /></a>
brew install node)~/Library/Application Support/Claude/claude_desktop_config.jsonYou can find this through the Claude Desktop menu:
Open Claude Desktop
Click Claude on the Mac menu bar
Click "Settings"
Click "Developer"
Add the following to your configuration:
{
"tools": {
"taskmanager": {
"command": "npx",
"args": ["-y", "@kazuph/mcp-taskmanager"]
}
}
}
brew install node)npm install -g tsx)git clone https://github.com/kazuph/mcp-taskmanager.git
cd mcp-taskmanager
npm install
npm run build
Make sure Claude Desktop is installed and running.
Install tsx globally if you haven't:
npm install -g tsx
# or
pnpm add -g tsx
~/Library/Application Support/Claude/claude_desktop_config.jsonAdd the following to your MCP client's configuration:
{
"tools": {
"taskmanager": {
"args": ["tsx", "/path/to/mcp-taskmanager/index.ts"]
}
}
}
The TaskManager supports two main phases of operation:
action: "plan" | "execute" | "complete"tasks: Array of task strings (required for "plan" action)taskId: Task identifier (required for "complete" action)getNext: Boolean flag to request next task (for "execute" action)// Planning phase
{
action: "plan",
tasks: ["Task 1", "Task 2", "Task 3"]
}
// Execution phase
{
action: "execute",
getNext: true
}
// Complete task
{
action: "complete",
taskId: "task-123"
}
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.