"A guide for replying to messages in Slack" matching MCP servers:

A Model Context Protocol server implementation that enables AI assistants to interact with Slack workspaces, allowing them to browse channels, send messages, reply to threads, add reactions, and retrieve user information.

Enables AI coding agents to communicate and coordinate through a durable, vendor-neutral message bus with support for threads, tasks, presence, and webhooks.

Enables structured team communication for Claude Code agents through Slack-like channels and direct messages. Supports project isolation, subscription management, and agent notes for sophisticated multi-agent collaboration workflows.

MCP server for posting messages to Slack channels via webhooks or bot API. Supports configurable usernames, emojis, and both webhook and bot token authentication modes.

Listens for Slack @mentions and publishes them as real-time events to the KĀDI event bus, enabling event-driven architectures with low latency.

Enables Codex to rank available tools and skills, rerank code and documentation search results, and triage saved output artifacts using Jev-based relevance scoring while leaving final decisions to Codex.

An MCP relay that adds a use_jev tool to every connected server, letting the Jev model autonomously select and execute tool calls while the calling model supplies any required text values. It enables agents to delegate multi-step tool use across all configured MCP servers through a single unified interface.

Enables Codex to manage a local Claude Code companion through MCP, implementing a dual-agent workflow where Codex handles reasoning and review while Claude Code performs engineering tasks.

Enables AI coding agents to request a second opinion from a different frontier model via a single tool call, with PII scrubbed before transit, live web search, and support for Claude, ChatGPT, Cursor, and Gemini.

Enables AI agents to control a Playwright-driven browser through natural-language instructions, including page interaction and live browser task execution.

Enables AI agents to request an independent second opinion from a different frontier model, with PII scrubbing before transit, live web search grounding, caching, and multi-provider failover.

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.

Orchestrates AI agents through structured markdown documents, enabling multi-agent workflows with automatic context injection and workflow management.

Human-in-the-loop approval gate for MCP agents, classifying tool calls by risk and requiring Slack-based human approval for medium/high risk actions.

Enables AI agents to drive real Google Chrome with stealth and captcha handling, using Patchright to avoid bot detection.

Enables ZCode to control a real Chrome browser, including tabs, navigation, page content, clicks, form filling, keyboard input, scrolling, screenshots, and JavaScript evaluation through a local MCP bridge.

Enables MCP clients to interact with A2A agents through four ordinary tools, translating agent discovery, messaging, task reading, and cancellation between the A2A and MCP protocols, with support for the tasks extension.

Enables OpenAI-compatible clients to access external tools, APIs, repositories, and data sources through MCP with allowlisting, approval, and argument validation, deployable as a FastAPI service or Python library.

Acts as a bridge between standard REST/OpenAPI web APIs and the Model Context Protocol, dynamically converting REST endpoints into MCP tools for LLM clients like Cursor, Claude Desktop, and n8n.

An MCP server that turns a one-sentence idea into working, tested code using a pipeline of six AI agents, with optional deployment.