"Task tracking tools for enabling LLMs to accomplish complex tasks" matching MCP servers:

Provides task and project management tools for AI agents, including todo list management, prioritization frameworks like Eisenhower Matrix and RICE scoring, time estimation using PERT, daily standup generation, and sprint burndown calculation.

Enables Claude/Lyra to create, monitor, and manage live sessions for long-running operations such as downloads, conversions, and agent jobs, with progress metrics, logs, error alerts, and a Textual dashboard; it also ingests updates from external media-server tools.

A generic MCP server for tracking any entity type (e.g., weight, workouts, books) without predefined schemas, using SQLite with JSON columns for flexible data storage and querying.

An MCP server that exposes the llms.txt file and its referenced local or external resources from a project root to provide context for AI models. It automatically parses documentation links and URLs to make them accessible as additional MCP resources.

Enables AI agents to perform local video, audio, and file operations inside an isolated workspace, including cutting/concat videos, extracting audio, transcribing, and managing files, with typed responses and background job support.

Enables natural language time tracking through Claude with markdown file storage. Supports multi-company tracking, flexible time parsing, auto-calculated summaries, and commitment warnings all through conversational input.

An MCP server that exposes outputty's task tracker as typed tools backed by GitHub Issues, allowing coding agents to manage tasks with two-way sync.

Enables LLMs to manage tasks in a local SQLite database, with tools for creating, listing, updating, and deleting tasks.

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.

Provides a task passport system for handoff across AI harnesses, enabling users to list, open, create, and checkpoint tasks with stable IDs and verified state.

Enables agents to manage a local SQLite task backlog over stdio, with tools to create, search, list, get, update, and stat tasks while preserving audit history and idempotency.

Provides an MCP interface to Google Tasks, enabling reading, creating, updating, and completing tasks and task lists, with support for date filtering to generate weekly reports.

A lightweight task management MCP server that enables CRUD operations on tasks stored in a single JSON file, including listing, creating, updating progress, and setting priorities.

Enables project and task management through a lightweight SQLite database, allowing users to create projects, add categorized tasks, track status changes, and get project statistics through natural language commands.

A gamified task management MCP server that mimics League of Legends ranked match system, enabling users to add tasks, complete them to spin a gacha, and earn or lose LP to change ranks.

A cross-AI-agent local task context sharing MCP server that allows clients like Codex, Claude Code, Hermes, and VS Code to read and write the same task state, enabling task tracking and context distillation.

A local Model Context Protocol server providing backend tools for AI agents to manage projects and tasks with persistent storage in SQLite, enabling structured tracking of project tasks with dependencies, priorities, and statuses.

MCP server for Google Tasks that enables reading, creating, editing, completing, reordering, and deleting tasks via the Google Tasks API.

Enables comprehensive task management with groups, custom statuses, and task relationships, designed for AI assistants to manage tasks during conversations.

Enables AI agents to read and manage a user's Google Tasks, including creating, editing, completing, moving, and deleting tasks and task lists via the Google Tasks API.