"Task" matching MCP servers:

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.

About Your task manager is the best agent memory you're not using. An agent-native context layer over your existing task app.

Improves AI agent task performance by providing task area segmentation, hierarchical RAG, and hybrid search capabilities.

Exposes task management (add, list, complete tasks) and document search (RAG) as MCP tools for AI agents.

Enables routing of ML tasks like chat, sentiment analysis, recommendations, and summarization to appropriate models through a dynamic YAML-based registry. Provides async FastAPI endpoints with streaming support, retry logic, and pluggable model architecture for scalable ML inference.

Integrates GitHub Copilot Chat with your Taskboard instance to manage workspaces, boards, lists, and cards using natural language. It supports full task lifecycle operations, searching capabilities, and knowledge base queries via RAG.

Enables running multiple Claude prompts simultaneously in parallel with support for file contexts and output redirection to individual files.

🤖 Taskade MCP · Official MCP server and OpenAPI to MCP codegen. Build AI agent tools from any OpenAPI API and connect to Claude, Cursor, and more.

Enables AI assistants to answer questions about the operator's current focus, engagements, reusable patterns, availability, and service offerings, with responses grounded in structured data and including confidence labels and source citations.

Enables users to search Samin Yasar's video library and receive full-video recommendations grounded in transcript evidence with links to exact matched caption cues.

An MCP server exposing internal business operations as tools — task management (create, list, update status) and RAG-style semantic search over an internal knowledge base (leave, expense, and onboarding policies) that any MCP-compatible AI agent can call directly for grounded, non-hallucinated answers.

ContextLattice is an HTTP-first, MCP-compatible memory/context/task orchestrator that persists writes and returns fused recall from specialized stores with local-first defaults. Primary URL: https://contextlattice.io/ Install: https://contextlattice.io/installation.html Troubleshooting: https://contextlattice.io/troubleshooting.html

Snap Router turns an agent's plain-language task into a ranked shortlist of the x402 services and MCP tools that actually serve it, in one ~200ms pass over the merged x402 Bazaar + MCP Registry catalog (16k+ entries) — no LLM call, with a "works well with" hint. The same server also ships Pricing-Truth: request-time on-chain liquidity and price integrity for Base/Ethereum/Arbitrum tokens -truth

A stdio MCP server that provides a single tool to query Gemini with Google Search grounding for current web information, returning synthesized answers with source links.

Local-first shared memory and task coordination for AI coding agents. One Go binary, MCP server, markdown files you own. Hooks for Claude Code and Codex CLI (and their desktop apps).

Enables AI coding agents to run Tavily-powered web searches and asynchronous, cited research through MCP, with tools for focused search, task creation, and status retrieval.

Enables AI assistants to search a curated database of 200+ AI tool cards with pricing, platforms, use cases, and source links, so users can ask which tool to use for a task and get grounded recommendations.

A high-performance MCP server providing long-term memory storage with semantic and keyword search, along with a structured agenda engine for task management.

Persistent shared memory for AI coding agents. Stores facts as entity/key/value triples with hybrid semantic search, task checkpoints, and conflict resolution — shared across Claude Code, Codex CLI, and GitHub Copilot.

A deep-research MCP server exposing a single task-augmented tool that runs GPT-Researcher with Tavily search, Anthropic Claude, and OpenAI embeddings, streaming progress via MCP tasks and Upjack entity stream.