"A platform for team communication and collaboration (Slack)" matching MCP servers:

In-memory MCP server for cooperative collaboration between separate agents, enabling topic-based messaging and coordination via tools like create_topic, join_topic, send_message, read_messages, and check_in.

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.

Brings live project context into Slack via MCP, enabling developer teams to check service health, recall team decisions, search code, and query project context directly from chat.

MCP Server for the Slack API, enabling Claude to interact with Slack workspaces.

MCP server for Slack workspace integration, exposing 40+ Slack operations as tools for Claude Desktop and providing a clean async Python API.

Enables Claude to collaborate with Gemini for code reviews, second opinions, and iterative software development. It facilitates multi-step workflows including PRD creation and code generation through an AI orchestration framework.

Enables collaboration between multiple AI models (GPT, Claude, Gemini) to work together on complex tasks, with intelligent task distribution and role-based expert assignment for code development, review, and optimization.

Enables building AI-powered Slack apps using the Slack MCP server and OpenAI models for automated messaging and canvas creation.

Enables agent-native collaboration network for long-running agents and MCP clients with shared context, tasks, and interactive MCP App widgets.

A simple Model Context Protocol server for Slack integration that enables messaging, channel management, and workspace search capabilities.

MCP server that exposes Slack Web API operations as tools, enabling users to list conversations, read history, post messages, and call any Slack Web API method.

MCP server for Slack that enables AI agents to interact with Slack workspaces, including listing channels, reading and posting messages, searching, managing users, reactions, and user groups.

Read and respond to Slack from Claude.

Enables AI assistants to interact with Slack workspaces by listing channels, posting messages and thread replies, adding emoji reactions, retrieving channel history and thread replies, and inspecting user profiles. Supports both stdio and Streamable HTTP transports for flexible integration.

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

Enables AI agents from different providers to collaborate in shared discussion threads, posting proposals and reviews while retrieving synchronized context, with human oversight.

Provides access to Atomic Red Team tests, enabling search, validation, and execution of atomic tests via natural language.

Enables bidirectional communication between MCP clients and Slack, allowing users to receive task notifications and respond to AI inquiries directly within Slack threads. It supports various urgency levels, message threading, and interactive question-and-answer workflows.

A read-only MCP server that enables AI agents to act as GCP platform engineers, allowing them to investigate incidents, take inventory, and find cost-optimization opportunities in Google Cloud projects without mutating any infrastructure.

An MCP server for semantic search and retrieval of indexed Slack messages stored in Qdrant using Cohere reranking via AWS Bedrock. It enables users to search through Slack history, retrieve full message threads, and access channel or user statistics through natural language.