TaskFlow 101 MCP Server

Model Context Protocol (MCP) server for task management, built with FastMCP. Integrate task management capabilities into Claude Desktop.

Local serverstdioPython

What is the TaskFlow 101 MCP server?

Model Context Protocol (MCP) server for task management, built with FastMCP. Integrate task management capabilities into Claude Desktop. The taskflow 101 mcp server wraps that behind the Model Context Protocol, so an assistant can use it through 9 defined tools rather than through you.

Its toolset

Everything the assistant can do here goes through one of these:

  • create_task — Create new tasks with full specifications
  • update_task_status — Update task status and track completion
  • get_task_details — Retrieve comprehensive task information
  • list_tasks_by_user — Filter tasks by assignee and status
  • get_overdue_tasks — Identify overdue items needing attention
  • search_tasks — Search across titles, descriptions, and tags
  • Resources — The Resources tool exposed by this server
  • Prerequisites — The Prerequisites tool exposed by this server
  • Installation — 1. Create and activate conda environment: bash conda create -n mcp-project python=3.10 conda activate mcp-project

Adding it to your client

mcp on PyPI is all you need. Most clients run it directly, so configuration is a few lines and a restart.

Configuration

  • Python 3.10+ - conda or pip (conda pref) - Claude Desktop (for integration)

When to reach for it

This sits in the planning and project tracking group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. TaskFlow 101's toolset — create_task, update_task_status, get_task_details and 6 more — is a fair guide to whether it matches your workflow. It is maintained by MuthuPalaniappan925; worth a glance at recent repository activity before you build anything load-bearing on it.

We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.

Caveats

  • It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
  • With 9 tools registered it takes up a noticeable share of the context window; turn it off in projects that never touch TaskFlow 101.
  • MCP clients confirm each tool call by default. Leave that on until you have watched what the taskflow 101 mcp server does with a few real requests.

Available tools

ToolWhat it does
create_taskCreate new tasks with full specifications
update_task_statusUpdate task status and track completion
get_task_detailsRetrieve comprehensive task information
list_tasks_by_userFilter tasks by assignee and status
get_overdue_tasksIdentify overdue items needing attention
search_tasksSearch across titles, descriptions, and tags
ResourcesThe Resources tool exposed by this server.
PrerequisitesThe Prerequisites tool exposed by this server.
Installation1. **Create and activate conda environment:** bash conda create -n mcp-project python=3.10 conda activate mcp-project

How to install the TaskFlow 101 MCP server

{
  "mcpServers": {
    "TaskFlow": {
      "command": "/path/to/your/project/.venv/Scripts/python.exe",
      "args": [
        "/path/to/your/project/main.py"
      ]
    }
  }
}

Configuration as documented by the project. Restart the client after saving.

Configuration

  • Python 3.10+ - conda or pip (conda pref) - Claude Desktop (for integration)

Example prompts to try

  • Use TaskFlow 101 to create task.
  • Use TaskFlow 101 to update task status.
  • Use TaskFlow 101 to get task details.

Frequently asked questions

It connects TaskFlow 101 to MCP-compatible AI assistants such as Claude and Cursor, exposing 9 tools (create_task, update_task_status, get_task_details, and more) that the assistant can call on your behalf. Instead of copying data back and forth by hand, the assistant works with TaskFlow 101 directly.