"Task" matching MCP servers:

Enables users to manage tasks through a simple JSON file interface. Provides basic task management functionality by reading and writing to a configurable tasks.json file.

A simple MCP server for managing tasks via a local JSON file, demonstrating resources, tools, and prompts for task reading, creation, and analysis.

Enables AI assistants to manage tasks across multiple projects with structured Markdown files, supporting creation, updates, completion, and organization with metadata and dependencies.

A straightforward task management system enabling sequential task tracking, completion, and progress management through simple function calls or natural language commands.

A comprehensive and efficient Model Context Protocol server for task management that works with Claude, Cursor, and other MCP clients, providing powerful search, filtering, and organization capabilities across multiple file formats.

Enables AI assistants to extract and query Obsidian Tasks from markdown files, supporting task metadata and advanced filtering via Obsidian Tasks query syntax.

Converts Cursor agent plans into structured markdown task lists and organizes them in your repository.

A Python-based MCP server for local Windows diagnostics, task management, cleanup, hardware inspection, security checks, and administrative workflows.

An MCP server for intelligent project planning and task management featuring task tracking, bug reporting, and feature specification with SQLite persistence. It includes full-text search capabilities and automatic filesystem synchronization to keep project data organized and accessible.

TaskFlow AI is a premium MCP Server designed for AI editors, offering 40+ built-in tools covering file system, HTTP requests, databases, Git operations, and more.

Enables natural language task management via Claude, allowing users to add, list, and complete tasks stored in a local JSON file.

A local evidence recorder that captures screenshots, recordings, notes, and summaries during long-running agent tasks, enabling reviewable task records with timelines and artifacts.

Enables AI models to manage file downloads with multi-threading, progress monitoring, and task control through standardized MCP interfaces.

Enables AI-native task management using plain markdown files to create, update, query, and organize Epics, Stories, Tasks, and Milestones without requiring a database.

Enables full management of ToDoList (.tdl) XML files with CRUD operations, hierarchical task support, and advanced filtering. Maintains compatibility with the ToDoList desktop application while allowing programmatic task management.

Provides LLMs with local filesystem operations (read/write files, list directories) and command execution via MCP, enabling file management and task automation within AI clients.

A comprehensive MCP server that enables AI models to perform local file operations, command execution, and task management across multiple platforms. It features advanced capabilities like row-level file editing, directory searching, and system monitoring with built-in security filters.

A Model Context Protocol server that wraps the official Obsidian CLI to allow AI agents to read, write, search, and manage notes within an Obsidian vault. It provides 16 specialized tools for comprehensive vault interaction, including note management, task tracking, and metadata manipulation.

A FastMCP-based server providing a comprehensive toolset for the RunningHub AI application platform. It enables users to configure nodes, upload media, submit AI tasks, and manage task execution and results through persistent storage.

A local, file-backed feature/bug board for projects, enabling Claude to read and write markdown boards (featurelist.md / buglist.md) directly in chat for task planning, bug logging, and velocity tracking.