"A tool for task summarization and team planning" matching MCP servers:

Provides intelligent summarization capabilities through a clean, extensible architecture. Mainly built for solving AI agents issues on big repositories, where large files can eat up the context window.

MCP server for team task tracking, code review, and activity monitoring via Claude Code. Assign tasks, track branch activity, review code, and get daily summaries through natural language.

Provides AI agents with a structured API for travel planning, enabling them to read trip data, search places, calculate routes, and create/validate itinerary change proposals that require explicit human approval before being applied.

Enables point-in-England lookups to retrieve planning designations such as conservation areas, listed buildings, green belt, flood risk zones, and more from the national planning data platform.

Enables LLMs to perform addition calculations through a stdio-based MCP server with an add_numbers tool and type-safe validation.

An MCP server for team documentation and knowledge bases, enabling semantic search over documentation files using local embeddings.

Provides comprehensive Australian planning property reports, including zoning, overlays, land size, and utility information for AI assistants. This high-performance MCP server is built for Cloudflare Workers and enables real-time property data retrieval through an HTTP-based interface.

Enables task management through MCP tools, resources, and prompts, backed by a PostgreSQL database.

An MCP server for Task Trellis that provides tools for AI coding agents to manage tasks, currently featuring a simple hello_world demonstration tool.

Enables Claude to interact with System Task projects, teams, and tasks, providing daily briefs, project reports, team load, and risk identification, as well as creating and updating tasks and demands.

Async MCP server for running long-running AI tasks with real-time progress monitoring, enabling users to start, monitor, and manage complex AI workflows across multiple models.

A tool discovery MCP server that integrates with Azure DevOps wikis and code-graph-rag to match natural language goals to tools, enabling tool composition and proxy testing.

An MCP server for task orchestration.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

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.

Elevate your LLM task management with Task Orchestrator, an MCP server that empowers you to define, organize, and track goals and tasks with hierarchical precision. Integrate intelligent task management into your workflow.

Enables LLMs to read and write local user data, generate fake users via sampling, and interact with structured prompts and resources.

Enables collaboration between multiple AI models (GPT, Claude, Gemini) to work together on complex tasks, with intelligent task distribution and role-based expert assignment for code development, review, and optimization.

Enables interaction with the Flow Team API through MCP clients, allowing endpoint discovery, API calls, and project management operations like listing projects and participants.

Publishes a shared MCP endpoint where API-key users in different groups see and call only the tools their policies permit, mixing remote upstream tools with local ones. Tool discovery and execution are both filtered, hidden-tool calls are denied before their handlers run, and every action is tagged with subject and group in structured JSON logs.