What can @sigmacomputing/slack-mcp-server do?

slack message sending via mcp protocol, slack channel and conversation retrieval via mcp resources, slack user and workspace metadata lookup, slack reaction and emoji interaction, slack thread and reply management, mcp server lifecycle and configuration management

@sigmacomputing/slack-mcp-server

MCP ServerFree

MCP server for interacting with Slack

Open Source

/ 100

6 capabilities

Capabilities6 decomposed

slack message sending via mcp protocol

Medium confidence

Enables LLM agents and tools to send messages to Slack channels and direct messages through the Model Context Protocol (MCP) transport layer. Implements MCP resource and tool schemas that map Slack API message endpoints to standardized function-calling interfaces, allowing Claude and other MCP-compatible LLMs to compose and dispatch messages without direct API credential handling.

Solves for

Send notifications from an AI agent to a Slack channel when a task completesHave an LLM compose and post formatted messages to Slack as part of a multi-step workflowEnable Claude to notify team members via Slack without exposing API keys to the LLM context

Best for

Teams building AI agents that need to notify Slack channels

Developers integrating Claude with Slack workflows via MCP

Organizations using Slack as a notification hub for AI-driven processes

Requires

Slack workspace with bot token (xoxb-*) with chat:write scope

MCP client implementation (e.g., Claude Desktop, custom MCP runner)

Node.js 18+ runtime for the MCP server process

Limitations

Message formatting limited to Slack's Block Kit and markdown syntax — no custom rendering

No built-in rate limiting or retry logic — relies on upstream MCP client for backpressure

Cannot send messages to private channels without explicit bot permissions configured in Slack workspace

What makes it unique

Wraps Slack Web API message endpoints as MCP tools with schema-based function calling, allowing LLMs to invoke Slack operations through standardized MCP resource definitions rather than direct API calls or custom prompt engineering

vs alternatives

Provides tighter LLM-Slack integration than generic Slack API wrappers because it uses MCP's typed tool schema to give Claude native understanding of Slack operations without requiring API key exposure in prompts

slack channel and conversation retrieval via mcp resources

Medium confidence

Exposes Slack channels, conversation history, and metadata as MCP resources that LLM agents can query and reference. Implements MCP resource URIs (e.g., slack://channel/C123) that map to Slack API list and history endpoints, enabling agents to discover channels, read recent messages, and extract context without manual API orchestration.

Solves for

Have an AI agent search for and read recent messages in a Slack channel to understand contextRetrieve a list of all channels in a workspace so an agent can decide which channel to post toExtract conversation history from a thread to use as context for generating a summary or response

Best for

AI agents that need to read Slack context before taking actions

Teams building Slack-aware assistants that reference recent conversations

Workflows where an LLM must discover channels dynamically based on workspace state

Requires

Slack bot token with channels:read, groups:read, and chat:history scopes

MCP client that supports resource URI dereferencing

Node.js 18+ for the MCP server

Limitations

Message history retrieval limited by Slack API pagination — typically 100 messages per request, requiring multiple calls for deep history

No real-time subscription to channel updates — agent sees snapshot at query time, not live changes

Private channel access depends on bot scopes (channels:read, groups:read) — cannot list or read channels the bot is not a member of

What makes it unique

Models Slack channels and messages as MCP resources with URI-based addressing, allowing LLMs to reference and query Slack data through the same resource abstraction layer used for files and documents, rather than treating Slack as a separate API silo

vs alternatives

Integrates Slack context retrieval into the MCP resource model, giving LLMs native ability to reference Slack conversations alongside other knowledge sources without custom prompt engineering or separate API client logic

slack user and workspace metadata lookup

Medium confidence

Provides MCP tools to query Slack workspace users, their profiles, and workspace metadata (name, plan, member count). Implements calls to Slack's users.list, users.info, and team.info endpoints wrapped as MCP function tools, enabling agents to resolve user mentions, check user status, and understand workspace context without direct API calls.

Solves for

Look up a user's email or profile information to mention them in a messageCheck if a user is active or away before deciding whether to notify themRetrieve workspace metadata to understand team size or plan tier for conditional logic

Best for

Agents that need to resolve user identities or check availability before messaging

Workflows that customize behavior based on workspace metadata or user status

Teams building Slack bots that reference user profiles or workspace context

Requires

Slack bot token with users:read and team:read scopes

MCP client supporting function tool invocation

Node.js 18+

Limitations

User status (active/away) is cached by Slack and may be stale by seconds to minutes

Profile fields are limited to what the workspace admin has configured — custom fields may not be present

Cannot retrieve user email without users:read scope, which requires workspace admin approval

What makes it unique

Exposes Slack user and workspace metadata as MCP tools with structured output schemas, allowing LLMs to query user profiles and workspace context as first-class operations rather than requiring agents to parse raw API responses or maintain user caches

vs alternatives

Provides structured, schema-validated access to Slack user and workspace data through MCP, reducing the need for agents to handle API pagination, error cases, or data transformation logic manually

slack reaction and emoji interaction

Medium confidence

Enables LLM agents to add, remove, and list emoji reactions on Slack messages through MCP tools. Wraps Slack's reactions.add, reactions.remove, and reactions.get endpoints as typed function calls, allowing agents to express sentiment, acknowledge messages, or trigger workflows based on emoji reactions without direct API credential exposure.

Solves for

Have an agent add a checkmark emoji to a message to indicate task completionRemove a reaction from a message if a condition changesCheck what reactions a message has received to gauge team sentiment or engagement

Best for

Agents that use emoji reactions as lightweight workflow signals or acknowledgments

Teams building interactive Slack bots that respond to or manage reactions

Workflows where emoji reactions serve as status indicators or voting mechanisms

Requires

Slack bot token with reactions:write and reactions:read scopes

Message timestamp and channel ID to target the message

MCP client supporting function tool invocation

Limitations

Can only add reactions to messages the bot has visibility of — cannot retroactively react to old messages outside bot's history window

Emoji name must match Slack's internal emoji namespace — custom emoji names must be looked up separately

No bulk reaction operations — each reaction requires a separate API call, making mass reactions slow

What makes it unique

Models emoji reactions as MCP tools with explicit add/remove/list operations, treating reactions as a first-class interaction mechanism rather than a side effect, enabling agents to use reactions as lightweight workflow signals or acknowledgment patterns

vs alternatives

Provides structured emoji reaction management through MCP, avoiding the need for agents to compose raw Slack API calls or manage reaction state manually, and enabling reaction-based workflows without custom prompt engineering

slack thread and reply management

Medium confidence

Allows LLM agents to post replies to message threads and retrieve thread context through MCP tools. Implements thread_ts parameter handling in message send operations and thread history retrieval, enabling agents to participate in conversations, maintain threaded discussions, and read full thread context without breaking conversation flow.

Solves for

Post a reply to a specific message thread rather than the channelRetrieve all messages in a thread to understand the full conversation contextHave an agent participate in a threaded discussion by reading and responding to thread messages

Best for

Agents that need to maintain threaded conversations and avoid cluttering channels

Teams using threads for organized discussions and wanting AI participation

Workflows where an agent must read thread context before responding

Requires

Slack bot token with chat:write and chat:history scopes

Parent message timestamp (thread_ts) to identify the thread

MCP client supporting function tool invocation

Limitations

Thread replies are only visible when expanding the thread — not visible in channel view, limiting discoverability

Cannot create a new thread from scratch — must reply to an existing message to start a thread

Thread history retrieval limited by Slack API pagination — deep threads require multiple API calls

What makes it unique

Treats Slack threads as first-class conversation containers in MCP, with explicit tools for thread reply posting and history retrieval, enabling agents to participate in threaded discussions while maintaining conversation context and organization

vs alternatives

Provides native thread support in MCP tooling, allowing agents to understand and participate in threaded conversations without custom logic to parse thread_ts or manage thread context manually

mcp server lifecycle and configuration management

Medium confidence

Implements the MCP server initialization, configuration, and transport layer for Slack integration. Handles stdio-based MCP protocol communication, tool and resource schema registration, and Slack API credential management through environment variables or configuration files. Manages the server lifecycle from startup through request handling and graceful shutdown.

Solves for

Deploy an MCP server that Claude Desktop or other MCP clients can discover and connect toConfigure Slack API credentials securely without exposing them in prompts or client codeRegister Slack tools and resources with proper MCP schemas so clients understand available operations

Best for

Developers deploying Slack integration as a standalone MCP server

Teams using Claude Desktop or custom MCP runners that need Slack connectivity

Organizations that want to centralize Slack API access through a single MCP server instance

Requires

Node.js 18+ runtime

Slack bot token provided via SLACK_BOT_TOKEN environment variable

MCP client implementation (Claude Desktop, custom runner, etc.)

Limitations

Stdio-based transport limits to single client connection per server instance — requires multiple server instances for concurrent clients

Credential management relies on environment variables — no built-in secret rotation or vault integration

No built-in logging or observability — debugging requires manual instrumentation or external logging setup

What makes it unique

Implements a complete MCP server wrapper around Slack API operations, handling protocol-level concerns (schema registration, request routing, error handling) so that Slack operations are exposed as native MCP tools without requiring clients to manage API details

vs alternatives

Provides a self-contained MCP server that abstracts away Slack API credential and protocol complexity, allowing MCP clients to interact with Slack through standardized tool schemas rather than managing API clients or credentials directly

Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.

Related Artifactssharing capabilities

Artifacts that share capabilities with @sigmacomputing/slack-mcp-server, ranked by overlap. Discovered automatically through the match graph.

MCP Server31

@sigmacomputing/slack-mcp-server

MCP server for interacting with Slack

slack channel and user lookup with context retrievalslack message sending via mcp protocolslack thread management and repliesslack conversation history retrieval with pagination

4 shared capabilities

MCP Server29

slack-relay-mcp

Code-execution-based Slack MCP tool — CLI + TypeScript API + Claude Code skill

mcp resource exposure for slack channels and messagesslack message relay via mcp protocolmulti-workspace slack support with workspace routingmcp tool schema for slack operations with function calling

4 shared capabilities

MCP Server42

slack-mcp-server

Model Context Protocol (MCP) server for Slack Workspaces. This integration supports both Stdio and SSE transports, proxy settings and does not require any permissions or bots being created or approved by Workspace admins

slack channel and user metadata exposure via mcp resourcesslack workspace message retrieval and search via mcpslack message posting and thread reply via mcp toolsmcp resource schema exposure for agent introspection

4 shared capabilities

MCP Server46

Slack MCP Server

Read and send Slack messages and manage channels via MCP.

slack workspace channel enumeration and metadata retrievalslack message posting with channel targetingmcp tool schema registration and json-rpc transportslack message history retrieval with thread context

4 shared capabilities

MCP Server23

Slack

** - Channel management and messaging capabilities. Now maintained by [Zencoder](https://github.com/zencoderai/slack-mcp-server)

slack channel listing and metadata retrievalmcp-compliant slack channel message postingmcp transport abstraction for slack api authentication

3 shared capabilities

Product17

Klavis AI

** - Open Source MCP Infra. Hosted MCP servers and MCP clients on Slack and Discord.

slack-native mcp client integration

1 shared capability

Best For

✓Teams building AI agents that need to notify Slack channels
✓Developers integrating Claude with Slack workflows via MCP
✓Organizations using Slack as a notification hub for AI-driven processes
✓AI agents that need to read Slack context before taking actions
✓Teams building Slack-aware assistants that reference recent conversations
✓Workflows where an LLM must discover channels dynamically based on workspace state
✓Agents that need to resolve user identities or check availability before messaging
✓Workflows that customize behavior based on workspace metadata or user status

Known Limitations

⚠Message formatting limited to Slack's Block Kit and markdown syntax — no custom rendering
⚠No built-in rate limiting or retry logic — relies on upstream MCP client for backpressure
⚠Cannot send messages to private channels without explicit bot permissions configured in Slack workspace
⚠Message history retrieval limited by Slack API pagination — typically 100 messages per request, requiring multiple calls for deep history
⚠No real-time subscription to channel updates — agent sees snapshot at query time, not live changes
⚠Private channel access depends on bot scopes (channels:read, groups:read) — cannot list or read channels the bot is not a member of

Requirements

Slack workspace with bot token (xoxb-*) with chat:write scopeMCP client implementation (e.g., Claude Desktop, custom MCP runner)Node.js 18+ runtime for the MCP server processSlack bot token with channels:read, groups:read, and chat:history scopesMCP client that supports resource URI dereferencingNode.js 18+ for the MCP serverSlack bot token with users:read and team:read scopesMCP client supporting function tool invocation

Input / Output

Accepts: text (message content), structured JSON (Slack Block Kit blocks), channel ID or user ID (string), channel ID (string, e.g., C123ABC), channel name (string, e.g., #general), optional limit parameter (integer) for message count, user ID (string, e.g., U123ABC), optional user email (string) for lookup, optional limit parameter for user list pagination, channel ID (string), message timestamp (string, e.g., 1234567890.123456), emoji name (string, e.g., 'thumbsup', 'checkmark'), thread timestamp (string, e.g., 1234567890.123456), reply message text (string), optional limit parameter for thread message count, environment variables (SLACK_BOT_TOKEN), MCP protocol messages (JSON-RPC over stdio)

Produces: JSON response with message timestamp and channel confirmation, error object with Slack API error code if delivery fails, JSON array of channel objects with metadata (name, topic, member count), JSON array of message objects with user, timestamp, and text fields, error response if channel is not accessible or does not exist, JSON user object with id, name, email, real_name, profile fields, is_active, is_away, JSON workspace object with name, plan, member_count, created timestamp, error response if user not found or insufficient permissions, JSON confirmation object with ok: true and reaction name, JSON array of reaction objects with emoji name and user count, error response if message not found or emoji invalid, JSON message object with timestamp and thread_ts confirmation, JSON array of message objects in the thread with full context, error response if thread not found or message cannot be posted, MCP protocol responses (JSON-RPC over stdio), tool and resource schema definitions (JSON), server initialization confirmation

UnfragileRank

Adoption40%(30% weight)

Quality14%(25% weight)

Ecosystem30%(25% weight)

Match Graph10%(15% weight)

Freshness75%(5% weight)

UnfragileRank is computed from adoption signals, documentation quality, ecosystem connectivity, match graph feedback, and freshness. No artifact can pay for a higher rank.

Type: MCP Server

6 capabilities

Visit @sigmacomputing/slack-mcp-server→

Package Details

npm

Registry

0.1.1

Version

5,249

Weekly Downloads

About

MCP server for interacting with Slack

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Capabilities6 decomposed

slack message sending via mcp protocol

Medium confidence

Solves for

Best for

Teams building AI agents that need to notify Slack channels

Developers integrating Claude with Slack workflows via MCP

Organizations using Slack as a notification hub for AI-driven processes

Requires

Slack workspace with bot token (xoxb-*) with chat:write scope

MCP client implementation (e.g., Claude Desktop, custom MCP runner)

Node.js 18+ runtime for the MCP server process

Limitations

Message formatting limited to Slack's Block Kit and markdown syntax — no custom rendering

No built-in rate limiting or retry logic — relies on upstream MCP client for backpressure

Cannot send messages to private channels without explicit bot permissions configured in Slack workspace

What makes it unique

vs alternatives

slack channel and conversation retrieval via mcp resources

Medium confidence

Solves for

Best for

AI agents that need to read Slack context before taking actions

Teams building Slack-aware assistants that reference recent conversations

Workflows where an LLM must discover channels dynamically based on workspace state

Requires

Slack bot token with channels:read, groups:read, and chat:history scopes

MCP client that supports resource URI dereferencing

Node.js 18+ for the MCP server

Limitations

Message history retrieval limited by Slack API pagination — typically 100 messages per request, requiring multiple calls for deep history

No real-time subscription to channel updates — agent sees snapshot at query time, not live changes

Private channel access depends on bot scopes (channels:read, groups:read) — cannot list or read channels the bot is not a member of

What makes it unique

vs alternatives

slack user and workspace metadata lookup

Medium confidence

Solves for

Best for

Agents that need to resolve user identities or check availability before messaging

Workflows that customize behavior based on workspace metadata or user status

Teams building Slack bots that reference user profiles or workspace context

Requires

Slack bot token with users:read and team:read scopes

MCP client supporting function tool invocation

Node.js 18+

Limitations

User status (active/away) is cached by Slack and may be stale by seconds to minutes

Profile fields are limited to what the workspace admin has configured — custom fields may not be present

Cannot retrieve user email without users:read scope, which requires workspace admin approval

What makes it unique

vs alternatives

Provides structured, schema-validated access to Slack user and workspace data through MCP, reducing the need for agents to handle API pagination, error cases, or data transformation logic manually

slack reaction and emoji interaction

Medium confidence

Solves for

Best for

Agents that use emoji reactions as lightweight workflow signals or acknowledgments

Teams building interactive Slack bots that respond to or manage reactions

Workflows where emoji reactions serve as status indicators or voting mechanisms

Requires

Slack bot token with reactions:write and reactions:read scopes

Message timestamp and channel ID to target the message

MCP client supporting function tool invocation

Limitations

Can only add reactions to messages the bot has visibility of — cannot retroactively react to old messages outside bot's history window

Emoji name must match Slack's internal emoji namespace — custom emoji names must be looked up separately

No bulk reaction operations — each reaction requires a separate API call, making mass reactions slow

What makes it unique

vs alternatives

slack thread and reply management

Medium confidence

Solves for

Best for

Agents that need to maintain threaded conversations and avoid cluttering channels

Teams using threads for organized discussions and wanting AI participation

Workflows where an agent must read thread context before responding

Requires

Slack bot token with chat:write and chat:history scopes

Parent message timestamp (thread_ts) to identify the thread

MCP client supporting function tool invocation

Limitations

Thread replies are only visible when expanding the thread — not visible in channel view, limiting discoverability

Cannot create a new thread from scratch — must reply to an existing message to start a thread

Thread history retrieval limited by Slack API pagination — deep threads require multiple API calls

What makes it unique

vs alternatives

Provides native thread support in MCP tooling, allowing agents to understand and participate in threaded conversations without custom logic to parse thread_ts or manage thread context manually

mcp server lifecycle and configuration management

Medium confidence

Solves for

Best for

Developers deploying Slack integration as a standalone MCP server

Teams using Claude Desktop or custom MCP runners that need Slack connectivity

Organizations that want to centralize Slack API access through a single MCP server instance

Requires

Node.js 18+ runtime

Slack bot token provided via SLACK_BOT_TOKEN environment variable

MCP client implementation (Claude Desktop, custom runner, etc.)

Limitations

Stdio-based transport limits to single client connection per server instance — requires multiple server instances for concurrent clients

Credential management relies on environment variables — no built-in secret rotation or vault integration

No built-in logging or observability — debugging requires manual instrumentation or external logging setup

What makes it unique

vs alternatives

Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.

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@sigmacomputing/slack-mcp-server

Capabilities6 decomposed

slack message sending via mcp protocol

slack channel and conversation retrieval via mcp resources

slack user and workspace metadata lookup

slack reaction and emoji interaction

slack thread and reply management

mcp server lifecycle and configuration management

Related Artifactssharing capabilities

@sigmacomputing/slack-mcp-server

slack-relay-mcp

slack-mcp-server

Slack MCP Server

Slack

Klavis AI

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

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@sigmacomputing/slack-mcp-server

Capabilities6 decomposed

slack message sending via mcp protocol

slack channel and conversation retrieval via mcp resources

slack user and workspace metadata lookup

slack reaction and emoji interaction

slack thread and reply management

mcp server lifecycle and configuration management

Related Artifactssharing capabilities

@sigmacomputing/slack-mcp-server

slack-relay-mcp

slack-mcp-server

Slack MCP Server

Slack

Klavis AI

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

Package Details

About

Categories

Alternatives to @sigmacomputing/slack-mcp-server

Are you the builder of @sigmacomputing/slack-mcp-server?

Get the weekly brief

Data Sources