slack-mcp-server
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- AlicenseBqualityCmaintenanceEnables AI assistants to interact with Slack workspaces, providing tools for reading messages, posting content, managing channels, and more.2239MIT
- FlicenseNot gradedqualityDmaintenanceEnables AI assistants to interact with Slack workspaces through natural language, supporting channel management, message operations, user profiles, reactions, and threaded conversations.-
- AlicenseAqualityDmaintenanceEnables AI assistants to interact with Slack workspaces through comprehensive channel management, messaging, direct messages, search functionality, and user management capabilities.306 npm2MIT
- FlicenseAqualityDmaintenanceEnables 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.17-
- FlicenseNot gradedqualityDmaintenanceEnables AI assistants to interact with Slack workspaces through secure OAuth 2.0 authentication. Supports posting messages, reading channel history, and listing channels across multiple workspaces with production-ready security features.-
- AlicenseAqualityDmaintenanceIntegrates 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.20169 npmMIT
TDQS
Scored across 10 tools
Each tool targets a distinct Slack operation: reacting, reading history, threads, user info, listing, posting, and replying. The two posting variants (plain vs markdown) are clearly differentiated, and reply tools also follow the same pattern. No ambiguity.
All tools consistently use the 'slack_' prefix followed by a clear verb_noun pattern in snake_case. Verbs like add, get, list, post, reply are used uniformly. Minor variation between 'get' and 'list' is acceptable and common.
With 10 tools, the set covers a broad but focused range of Slack interactions (message reading/writing, reactions, user and channel info) without being overwhelming or sparse. Each tool feels necessary for typical agent tasks.
Core operations are well-covered: reading channels/threads, posting messages, reacting, and retrieving user/channel info. Missing update/delete message capabilities and search, but these are not critical for common use cases, making the surface mostly complete.