"Slack 메시지에서 태그된 항목 조회 및 요약 방법" matching MCP servers:

Enables coding agents to query the dependency graph of a GitHub backlog, retrieve ordered ready work and prerequisite chains, atomically claim issues, and report blockers—so agents work in the correct order and safely in parallel.

Slack Agent Mesh is an open-source MCP server that turns a single Slack app into a mesh of virtual agent identities, providing a transport and coordination layer where agents can be addressed by name and collaborate through durable, human-visible Slack threads.

An MCP server that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.

Enables AI agents to request human decisions and send notifications through chat platforms like Slack and WhatsApp, with ephemeral in-memory pending requests and no central backend.

An MCP server that enables local AI models to receive guidance from remote 'senior' AI providers like OpenAI, Anthropic, and Gemini to solve programming problems. It features intelligent multi-turn dialogue management, context synchronization, and automated session history tracking.

Tracks meeting commitments, verifies completion via Slack/email/Linear, and sends escalating nudges with manager escalation when deadlines slip.

An MCP server that acts as an AI assumption firewall, intercepting risky decisions, detecting contradictions, and routing human approval requests via Telegram or Slack.

Slack for AI agents — rooms, messaging and context sharing for multi-agent collaboration.

Multi-workspace Slack MCP server with draft+confirm safety, vault auto-export, and triple-mode auth.

A TypeScript MCP server that integrates Devin AI with Slack, allowing users to create Devin sessions, post tasks to Slack channels, and maintain thread context between Devin sessions and Slack threads.

Enables coding agents to add a bounded semantic-judgment layer for routing, ranking, extraction, verification, and escalation, returning typed signals and review recommendations.

An AI personality collaboration tool based on Model Context Protocol (MCP) that enables users to summon and collaborate with multiple AI personas for intelligent analysis and problem-solving.

Autonomous QA testing MCP server that analyzes, fixes, and learns from test failures. Integrates with IDE and Slack to provide cause and fix in plain language.

缔零法则MCP是基于LLM和RAG技术搭建的实现完全替代人力的全自动化风险识别的内容安全审查平台，致力于通过代理AI技术减少人力成本，高效高精度为用户提供分钟级接入的内容风控解决方案，破解安全威胁，提供从风险感知到主动拦截策略执行的全链路闭环与一体化解决方案。This MCP tool is an AI-powered content security review platform built on LLM and RAG technologies, designed to achieve fully automated risk identification that completel

MCP server for async messaging between AI coding agents, enabling cross-harness and cross-machine communication with Slack-like semantics and mail-shaped delivery.

Enables autonomous AI agents to operate safely by intercepting risky tool calls, evaluating them against policy, and suspending them for human approval via Slack, Telegram, or a web dashboard.

Pauses AI agent execution and routes approval requests to humans via Slack or email, with cryptographically signed proof of the human's decision.

Enables plain-English workflow automation across connected tools like GitHub, Notion, Slack, and more, with self-healing execution, scheduling, and status reporting through MCP.

Enables autonomous Jira-to-PR workflows in Claude Code by fetching context from Jira, GitHub, Notion, and Slack, building structured prompts, and handling branch pushes, PR creation, CI polling, and task completion.

OAuth token broker for AI agents to securely act on a user's behalf across third-party APIs (Gmail, Slack, GitHub, Notion, etc.) by vaulting tokens server-side and never exposing them to the LLM.