AgentRQ: Human-in-loop realtime conversational task manager for AI Agents. Self-hosted! Control your own agents from wherever you want Mobile, Web, Desktop. Designed to work well with your own Claude subscriptions and any harness with ACP support.

Local MCP server for Google Workspace (Gmail, Drive, Calendar, Sheets, Docs, Contacts, Tasks, Meet, Search Console, +Forms/Chat/Admin) across multiple accounts — OAuth-only, encrypted token storage, deny-by-default writes.

Self-hostable AGPL workspace where humans and AI agents share chat, tasks, knowledge, approvals, and MCP context.

ClickUp MCP Server - Powering AI Agents with full ClickUp task, document, and chat management capabilities.

A Model Context Protocol (MCP) server for ATLAS, a Neo4j-powered task management system for LLM Agents - implementing a three-tier architecture (Projects, Tasks, Knowledge) to manage complex workflows. Now with Deep Research.

Deterministic, persistent graph server for tracking workflow state, decisions, and blockers.

Shared team knowledge, leaked-secret alerts, ranked code findings and tracked tasks, across every AI coding tool you use

LeanCTX is the Context Gateway for AI Systems. Select task-relevant context, apply supported controls, connect local knowledge and inspect recorded evidence. Open-source Engine: CLI, MCP, hooks and supported proxy paths.

Vibe Check is a tool that provides mentor-like feedback to AI Agents, preventing tunnel-vision, over-engineering and reasoning lock-in for complex and long-horizon agent workflows. KISS your over-eager AI Agents goodbye! Effective for: Coding, Ambiguous Tasks, High-Risk tasks

Turn any laptop, desktop, VM, or server into a secure AI-agent workspace via MCP. Let ChatGPT, Claude, Grok, Qwen and other MCP clients read and edit files, run commands, test code, inspect systems, and complete real-world tasks.

MCP server that lets Claude Code delegate heavy-token tasks to DeepSeek, Kimi, GLM, Qwen, Grok, or any OpenAI-compatible model. Claude orchestrates; the delegate does the heavy lifting. Zero dependencies.

Enables Claude Code to delegate tasks to persistent GitHub Copilot CLI sessions via MCP, inspect pending tool requests, and approve each operation once or deny it while continuing multi-turn context. It bridges ACP runtime sessions locally over stdio without a public service or background daemon.

Enables Claude and ChatGPT to manage Motion tasks through one shared API core, including capturing next actions, preserving resume context, checking duplicates, and reporting scheduling health. It serves local stdio clients and OAuth-protected Streamable HTTP clients.

Turns any OpenAPI spec into a single-tool MCP server where the model writes JavaScript against a typed api object in a QuickJS sandbox, so multi-step tasks run in one round trip and only the final result reaches context. Credentials, rate limiting, retries, write gating and audit logging stay on the host, outside the sandbox.

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.

Enables Claude chat and Claude Code sessions to exchange tasks, tickets, and project context through a local inbox, including threads, project cards, session status, and shared markdown context.

The fullstack TypeScript framework for MCP and APIs — write one action, serve HTTP, WebSocket, CLI, background tasks, and MCP tools.

GodPrompt MCP server + portable Agent Skill for coding agents — TDD, debugging, verification gates, task routing, and progressive disclosure.

Self-hosted work log your team's AI agents write: daily updates drafted from git and the session, tasks, time measured from agent sessions, project context and client access. 39 tools over Streamable HTTP, with personal keys for coding agents and OAuth for the Claude and ChatGPT apps.

Enables MCP clients to coordinate local AI model runs by monitoring RAM, system commit, and VRAM, queueing tasks across clients, performing admission checks before inference, renewing leases, completing and releasing runs, and reporting status, history, and health while preserving original generation quality parameters. It also supports controlled start/stop and optional idle application memory reclamation.

Enables building zero-dependency Model Context Protocol servers over the Streamable HTTP transport, exposing typed tools, resources and URI templates, prompts, background tasks, and OAuth-protected endpoints. It can be mounted into FastAPI, Starlette, Flask, Django or any ASGI/WSGI app, or run standalone on the Python standard library alone.

Enables AI coding agents to automatically compress context at agent-judged task boundaries, write incremental structured session snapshots, and maintain per-fact long-term memory for priority restoration across sessions.

Enables deterministic execution, cryptographic security, and game-theoretic optimization through the Model Context Protocol, returning deterministic JSON tool results for agent telemetry and task inputs.

Shared memory for your AI tools: tasks, notes and context every tool can read and write over MCP.