"General search for the term 'task'" matching MCP servers:

Provides LLMs with full PostgreSQL database access, including tools for query execution, schema management, and data export. It also features a dedicated insights system for storing business memos and supports both local stdio and remote HTTP transport.

Provides AI coding agents with a read-only live view of a project's task state, including progress, blockers, and evidence, via zero-token conditional polling and an optional widget for rendering a dashboard card.

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.

MCP server for managing i18n translation files — gives your AI agent full control over your app's translations without dumping entire locale files into context.

MCP server for OpenClaw task lifecycle management, enabling starting, listing, and checking status of tasks via a Gateway API.

A Model Context Protocol implementation that provides a standardized interface for task management, supporting both STDIO mode for CLI/AI applications and HTTP+SSE mode for browser-based clients.

A campaign and task management MCP server for AI coding assistants, enabling dependency tracking, acceptance criteria, testing strategies, and progress monitoring for projects.

A Model Context Protocol server for intelligent task management in AI-powered development environments, providing file-based storage, dependency management with cycle detection, and an interactive CLI.

A secure MCP server providing controlled access to pixi tasks and commands, eliminating agent bash circumvention. It exposes 11 pixi tools through 4 meta-tools for ~95% context savings.

A task manager MCP server that demonstrates core MCP concepts (resources, tools, prompts, stdio) and syncs data with a Next.js web app.

A secure, vector-based task management server for Claude Desktop using sqlite-vec and sentence-transformers. It provides intelligent task tracking with semantic search capabilities to organize and retrieve development tasks efficiently.

Enables AI agents to decompose high-level goals into structured task plan DAGs with dependencies, acceptance criteria, and quality gates, and to validate or export those plans in multiple formats.

Enables intelligent task management with status tracking, dependency resolution, and automatic next task discovery based on preconditions and priorities. Supports hierarchical task structures with subtasks and flexible JSON-based configuration.

A local task management MCP server that enables users to create, update, and manage tasks through natural language conversations with Claude. It provides nine tools for comprehensive task management including creation, filtering, searching, and daily planning without requiring a separate UI or backend service.

An MCP server that automates project task breakdown, dependency management, and smart task recommendations, integrating with LLMs like Gemini and OpenAI.

MCP server for Nova Agent progress reporting. Enables updating execution sessions and managing steps within tasks.

A task manager MCP server that demonstrates all three MCP primitives (tools, resources, prompts). Enables users to manage tasks, read task summaries and details, and run structured planning/review prompts through natural language.

Enables AI agents to autonomously manage and improve execution processes for repetitive task types by storing reusable task contexts with associated artifacts (practices, rules, prompts, learnings) and providing full-text search across historical best practices.

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 Shrimp Task Manager is a task tool built for AI Agents, emphasizing chain-of-thought, reflection, and style consistency. It converts natural language into structured dev tasks with dependency tracking and iterative refinement, enabling agent-like developer behavior in reasoning AI systems.