"Slack Bot with RAG Document Retrieval and Automated Response System" matching MCP servers:

Enables comprehensive Slack workspace integration through AI assistants, allowing users to manage channels, send messages, upload files, search conversations, and interact with users through natural language commands.

Enables comprehensive interaction with Slack workspaces, allowing users to manage channels, send messages, and search history. It supports managing reminders, pins, reactions, and user information through the Model Context Protocol.

An AWS-native MCP server that posts to Slack (post_to_slack, post_file_to_slack) via an Amazon Bedrock AgentCore Gateway.

Enables interaction with Slack workspaces through comprehensive integration capabilities. Supports channel management, messaging, thread replies, reactions, and message history retrieval through natural language commands.

A Model Context Protocol server that integrates with Slack API, allowing users to send messages, view channel history, manage channels, send direct messages, and retrieve user lists from Slack workspaces.

Enables automated giveaway entry management by parsing live campaigns, mapping each entry method to configured credentials, submitting signed HTTP entries, handling mandatory chains, and performing required X actions. It exposes these capabilities as MCP tools for AI agents or scripts, including cookie/session checks, dry-run planning, and multi-account workflow support.

MCP server that connects Claude Code to Slack, allowing two-way communication via Slack Socket Mode without tunnels.

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.

Enables AI assistants to interact with Slack workspaces through comprehensive channel management, messaging, direct messages, search functionality, and user management capabilities.

Integrates AI assistants with Slack workspaces using OAuth 2.0 authenticated user tokens for secure, multi-functional interaction. It enables comprehensive operations including channel management, message searching, file handling, and reaction management through natural language.

Enables interaction with Slack workspaces as a user, supporting channel listing, message posting, threading, reactions, and user management via the Slack API.

Enables interaction with Slack workspaces to manage channels, post messages, add reactions, view message history and threads, and retrieve user profiles through the Model Context Protocol.

An MCP server that provides comprehensive access to the Slack Web API, enabling AI agents to search messages, manage channels, and create canvases. It features 13 core tools and over 300 dynamic methods for complete automation of Slack workspace operations.

A connector enabling Claude Desktop or any MCP client to interact with Slack workspaces to post messages and query user lists.

MCP Server for send text/markdown message via dingding (aka dingtalk) group custom robot

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

Enables Claude AI to send real-time notifications to Slack channels with support for rich formatting, multiple channels, and customizable message styling for workflow automation and task completion alerts.

Enables AI agents to create, validate, and export UML system models using structured MSON format. Supports generating PlantUML and Mermaid diagrams with direct export to System Designer macOS application.

Enables MCP clients to send plain-text messages to a preconfigured WeCom group chat bot through a single send tool. It validates content size, restricts delivery to the configured webhook, and returns platform acceptance or error status without retries or persistence.

Lets MCP clients such as Claude Code, Codex, Cursor, and VS Code drive the Grok Bot desktop app on macOS by listing the user's bots, reading their chats, sending them messages, and answering their multiple-choice questions locally without API keys. All actions run live in the real app via the macOS Accessibility API, with no network calls, telemetry, or dependencies.