"Information on memory banks or task managers" matching MCP servers:

Provides persistent project memory, task lists, time tracking, and shared rules and learned preferences so coding agents can recall decisions and conventions across sessions and coordinate multi-step work.

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 querying FDIC-insured institutions, their Call Report financials, peer comparisons, failure records, and deposit market share via MCP, over stdio or Streamable HTTP.

Enables extracting explicitly stated contract metadata, clauses, and obligations from user-supplied contract text without storing or modifying the data.

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

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.

An MCP server for task orchestration.

Enables AI to directly manage tasks, tags, categories, and projects in the xx-task desktop app's SQLite database, offering full CRUD operations through MCP tools.

Bridges the ChatGPT web UI to a local development environment over MCP, letting the model read and patch files, run real shell commands and terminals, execute tests, and control the desktop (screen, mouse, keyboard, clipboard) within user-approved folders. It adds parallel workers, goal/loop long-task control, plugin tools, and a security-hardening layer with risk-tiered shell policy, audit logging, and credential sanitization.

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.

Enables running a stateless Model Context Protocol server over Streamable HTTP on Cloudflare Workers or any fetch-capable runtime, with signed sessions, origin checks, and JSON-RPC request handling. It lets developers define tools with JSON Schema validation and per-request context.

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

Enables MCP-compatible AI clients and coding agents to turn vague GitHub requests into structured, testable task contracts, inspect repository evidence, simulate execution, validate readiness, and preview or publish Gibwork bounties only after explicit confirmation.

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

Enables AI assistants to manage Dida365 (滴答清单) tasks through the Model Context Protocol. It supports full task lifecycle management including creating, updating, and filtering tasks with automatic timezone handling.

MCP server that wraps a personal task manager REST API, enabling Claude to read and manage tasks via tools like get_tasks and add_task.

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.

MCP server deployed on EdgeOne Pages, providing a Streamable HTTP MCP server for intelligent chat applications with tool capabilities like generating webpages.

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.

Provides AI agents with persistent, searchable memory using semantic search, auto-linking, and categorization, with zero-config local setup or production-ready external providers.

Enables agents to discover and retrieve contract details for Task Relay F1-F5 paid x402 machine jobs, but does not execute work or handle payments.

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.

Provides persistent memory for AI assistants via MCP, enabling them to store and recall facts, preferences, and tasks across conversations using either local file storage or a cloud backend with semantic search.

MCP server for Apple Notes enabling read, search, write, and sync of notes with high fidelity, including styles, attachments, and bidirectional Markdown sync.

This MCP server enables agents to manage complex tasks by providing tools for registration, complexity assessment, breakdown into subtasks, and status tracking throughout the task lifecycle.

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.

Enables AI assistants to manage tasks through a comprehensive interface with 8 tools for creating, updating, searching, and tracking tasks with priorities, categories, and due dates. Features persistent file-based storage, advanced filtering, and task statistics for complete task management workflow.

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

Enables task management via MCP tools for creating, listing, updating, completing, and deleting tasks with JSON file storage.

An MCP server that provides AI assistants with persistent, semantic memory using Turso for storage and OpenAI for vector search. It enables natural language operations to store, retrieve, and refine information with automatic duplicate detection and quality validation.

An MCP server that lets users capture quick phone thoughts via Android and later query them from AI assistants like Grok or Claude, functioning as a simple task memory store without notifications or geolocation.

A fully local persistent memory layer for LLM coding agents (Claude Code, Codex, Gemini CLI, OpenCode). A shell wrapper intercepts tool invocations, fires hooks on every tool call, then runs a 3-layer pipeline (extract → compress to ≤500-token digest → merge into project memory doc) at session end. The next session gets prior context injected automatically.

Open Task Relay provides free, bounded public-good tasks that autonomous AI agents can discover, complete, submit, and independently verify. Its public TypeScript source runs locally with a Cloudflare Workers-compatible runtime and SQLite/D1, exposing MCP over HTTP.

Enables AI agents to report task lifecycle events—start, progress, waiting, rename, and terminal outcomes—so a single Huawei Today screen card stays updated per task under one task_id. Delivers these notifications through a self-hosted Cloudflare Workers deployment with OAuth-scoped agents, queued retries, and an admin console for notification policies.

A fully-local AI memory system that saves notes, code, and terminal output to a vector database via Ollama and LanceDB, enabling context retrieval from terminal, API calls, or inside Claude Code.

Shared, live team memory for Claude — a remote MCP server on Cloudflare Workers + D1.

A local, persistent memory system for AI coding assistants that stores decisions, patterns, and session context via MCP tools. It enables cross-session memory management using SQLite and optional vector search without external dependencies or cloud storage.

Connects ChatGPT to local files, terminals, and the desktop through MCP with Chrome integration, letting users read and edit project files, run commands, and follow tool results as they arrive. It also adds durable multi-agent workers, Goal/Loop task tracking, mid-task corrections, and Compact & Resume for carrying session and worker history into a fresh chat.

Provides a persistent memory layer for Stellar and Soroban projects, scanning repositories to create a knowledge graph of contracts, storage, and on-chain state. Exposes this memory to AI agents via MCP, enabling project overview, search, and context recovery.