mcp-slack
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- AlicenseBqualityCmaintenanceEnables AI assistants to interact with Slack workspaces, providing tools for reading messages, posting content, managing channels, and more.2238MIT
- AlicenseAqualityCmaintenanceEnables AI assistants to interact with Slack workspaces, including listing channels, posting messages, replying to threads, adding reactions, and retrieving user information.1014 npmMIT
- AlicenseAqualityCmaintenanceEnables interaction with Slack workspaces as a user, supporting channel listing, message posting, threading, reactions, and user management via the Slack API.811MIT
- AlicenseNot gradedqualityCmaintenanceProvides Slack workspace integration tools for AI agents, enabling channel listing, message history retrieval, sending messages, user listing, and channel joining through natural language.4 npmMIT
- FlicenseAqualityDmaintenanceEnables AI agents to interact with Slack using a user token, providing full access to message search, channel history, DMs, and posting as the user.8-
- FlicenseNot gradedqualityDmaintenanceProvides complete Slack Web API integration with 9 tools for reading messages, managing channels, searching content, and interacting with Slack workspaces.-
TDQS
Scored across 3 tools
Each tool maps to a distinct Slack action+resource: listing channels, reading messages, and posting messages. There is no overlap in purpose or argument shape between them.
All three tools use a consistent slack_ prefix with a clear verb_noun pattern (slack_list_channels, slack_read_channel, slack_post_message). The convention is predictable throughout.
Three tools is on the thin side for a Slack integration; the set covers only the most basic read/write loop. It is functional but leaves little room for common adjacent operations.
Core operations (list channels, read messages, post message) are present, but there are notable gaps: no thread replies, reactions, message search, user/DM lookup, or message editing. Agents can do basic workflows but will hit dead ends on common Slack tasks.