What can Slack MCP Server do?

slack workspace channel enumeration via mcp protocol, slack message history retrieval with thread context, slack message posting with formatting and metadata, slack thread reply composition with context awareness, slack message reaction management (add/remove emoji reactions), mcp protocol transport and tool schema exposition, slack authentication and token management via mcp context, slack api error handling and resilience with mcp error responses

Slack MCP Server

MCP ServerFree

Read and send Slack messages and manage channels via MCP.

Open Source

/ 100

8 capabilities

Capabilities8 decomposed

slack workspace channel enumeration via mcp protocol

Medium confidence

Exposes a standardized MCP tool that lists all accessible channels in a connected Slack workspace by querying the Slack Web API's conversations.list endpoint. The server implements the MCP Tools primitive to surface this capability as a callable function with JSON-RPC transport, enabling LLM clients to discover and introspect channel metadata (name, topic, member count, archived status) without direct API knowledge. Uses Slack SDK for TypeScript to handle authentication via bot token and pagination of large channel lists.

Solves for

I need my AI agent to discover which Slack channels exist in our workspace before routing messagesI want to list all channels matching certain criteria (archived, public, private) to understand workspace structureI need to programmatically find a specific channel by name to post updates there

Best for

AI agents and assistants that need workspace awareness before taking Slack actions

Teams building multi-channel notification systems with LLM orchestration

Developers integrating Slack into MCP-based AI workflows

Requires

Slack workspace with bot user created

Bot token with 'conversations:read' scope

MCP client that supports the Tools primitive

Limitations

Pagination is automatic but large workspaces (10k+ channels) may incur multiple API calls with latency

Returns only channels the bot token has permission to view; private channels require explicit membership

No filtering on the server side — clients must filter results themselves

What makes it unique

Implements channel listing as a first-class MCP tool rather than a raw API wrapper, meaning the capability is discoverable and callable by any MCP-compatible client (Claude, custom agents) without requiring direct Slack SDK knowledge. Uses MCP's standardized tool schema to abstract away pagination and error handling.

vs alternatives

Simpler than building direct Slack API integrations because MCP handles transport, authentication context, and tool discovery; more discoverable than raw webhooks because the tool is self-describing in the MCP protocol.

slack message history retrieval with thread context

Medium confidence

Implements an MCP tool that fetches message history from a specified Slack channel using the conversations.history API, with optional thread-aware context retrieval via replies.list. The server accepts channel ID and optional timestamp range parameters, returning paginated message objects including user ID, timestamp, text content, and thread metadata. Handles both flat channel history and nested thread replies, enabling LLM clients to read conversation context before responding or analyzing.

Solves for

I need to read recent messages in a channel to understand context before posting a responseI want to fetch all replies in a specific thread to provide comprehensive context to an AI modelI need to retrieve messages from a date range to analyze conversation patterns or extract information

Best for

AI assistants that need to read Slack conversation history before generating responses

Chatbots that require thread context to maintain conversation coherence

Analytics and monitoring agents that analyze Slack communication patterns

Requires

Slack bot token with 'channels:history' and/or 'groups:history' scopes

Valid channel ID (not channel name)

MCP client implementation

Limitations

API rate limits apply (typically 1 request per second per workspace); large history requests may require backoff

Message content is limited to what Slack stores; deleted messages are not retrievable

Thread replies require separate API call (replies.list), adding latency for deep thread context

What makes it unique

Combines channel history and thread reply retrieval into a single MCP tool abstraction, handling the complexity of nested Slack conversation structure (flat messages vs threaded replies) transparently. The server manages pagination and scope validation, exposing a unified interface rather than requiring clients to call multiple Slack APIs.

vs alternatives

More context-aware than simple message fetching because it supports thread-aware retrieval; more efficient than raw Slack API calls because the MCP server can batch and cache common queries.

slack message posting with formatting and metadata

Medium confidence

Exposes an MCP tool that posts messages to a Slack channel using the chat.postMessage API, supporting plain text, markdown, and Slack's Block Kit JSON formatting. The server accepts channel ID, message text, and optional parameters (thread timestamp for replies, metadata for custom fields, reply broadcast flag). Handles message composition, formatting validation, and returns the posted message timestamp for reference or threading.

Solves for

I want my AI agent to post a formatted notification or response to a specific Slack channelI need to reply to a thread with context-aware content generated by an LLMI want to post rich-formatted messages (buttons, sections, images) from an AI workflow

Best for

AI agents that need to communicate results or alerts back to Slack users

Chatbots that generate responses and post them to channels or threads

Automation workflows that need to notify teams of events or decisions

Requires

Slack bot token with 'chat:write' scope

Valid channel ID (not channel name)

Message text content (plain text or Block Kit JSON)

Limitations

Message size is limited to 4000 characters for plain text; Block Kit payloads have separate size limits

Bot token must have 'chat:write' scope; cannot post to private channels without explicit membership

Formatting support depends on Slack client version; some Block Kit features may not render in older clients

What makes it unique

Abstracts Slack's chat.postMessage API as an MCP tool, allowing LLM clients to post messages without handling authentication, formatting validation, or error recovery. Supports both simple text and complex Block Kit JSON, enabling rich UI composition from AI-generated content.

vs alternatives

More flexible than webhook-based posting because it supports threading, metadata, and dynamic formatting; more discoverable than raw API calls because the tool schema is self-describing in MCP.

slack thread reply composition with context awareness

Medium confidence

Implements an MCP tool that posts replies to Slack threads using chat.postMessage with thread_ts parameter, enabling LLM clients to respond within conversation threads while optionally broadcasting replies to the channel. The server validates thread timestamp, handles reply-specific formatting, and manages the relationship between thread context and channel visibility. Supports both private thread replies and broadcast replies that appear in both thread and channel.

Solves for

I want my AI assistant to reply to a specific message in a thread without cluttering the channelI need to post a response that's visible both in the thread and in the channel (broadcast reply)I want to maintain conversation coherence by keeping related messages in the same thread

Best for

Conversational AI agents that need to maintain thread-based discussions

Support bots that respond to user questions within existing threads

Multi-turn dialogue systems where context is organized by thread

Requires

Slack bot token with 'chat:write' scope

Valid channel ID

Valid thread_ts (message timestamp of the thread root)

Limitations

Thread timestamp (thread_ts) must be valid and correspond to an existing message; invalid timestamps fail silently

Broadcast replies (reply_broadcast=true) are visible in channel but may create notification fatigue

Thread replies cannot be edited via this tool; requires separate chat.update API

What makes it unique

Treats thread replies as a first-class MCP capability separate from channel posting, recognizing that Slack's threading model requires explicit thread_ts handling. The server abstracts away the complexity of broadcast vs private replies, allowing clients to specify intent (thread-only or broadcast) without API-level details.

vs alternatives

More conversation-aware than generic message posting because it enforces thread context; simpler than managing thread state manually because the MCP server handles timestamp validation and broadcast logic.

slack message reaction management (add/remove emoji reactions)

Medium confidence

Exposes MCP tools for adding and removing emoji reactions to Slack messages using the reactions.add and reactions.remove APIs. The server accepts channel ID, message timestamp, and emoji name, managing the relationship between message identity (channel + timestamp) and reaction state. Supports standard Slack emoji names and custom emoji, with error handling for invalid emoji or permission issues.

Solves for

I want my AI agent to acknowledge a message with an emoji reaction (e.g., thumbs up for approval)I need to remove a reaction that was added in error or is no longer relevantI want to use reactions as a lightweight feedback mechanism for AI-generated responses

Best for

AI agents that need lightweight feedback mechanisms without posting messages

Chatbots that acknowledge user requests with emoji reactions

Automation workflows that mark messages as processed or reviewed

Requires

Slack bot token with 'reactions:write' scope

Valid channel ID

Valid message timestamp (ts)

Limitations

Emoji name must be valid Slack emoji (standard or custom workspace emoji); invalid names fail with error

Bot token must have 'reactions:write' scope; cannot add reactions to messages in channels the bot cannot access

Removing a reaction that doesn't exist returns success but has no effect

What makes it unique

Implements reaction management as discrete MCP tools (add and remove) rather than a single toggle, giving clients explicit control over reaction state. The server validates emoji names and handles Slack's idempotent reaction semantics, where adding a duplicate reaction is a no-op.

vs alternatives

Lighter-weight than message posting for simple acknowledgments because reactions don't create notification noise; more discoverable than raw API calls because the tool schema is self-describing in MCP.

mcp protocol transport and tool schema exposition

Medium confidence

Implements the Model Context Protocol server-side transport layer using TypeScript SDK, exposing all Slack capabilities as standardized MCP Tools with JSON-RPC 2.0 communication. The server registers tool handlers, manages request/response serialization, and implements the MCP initialization handshake. Supports stdio and SSE (Server-Sent Events) transport mechanisms, allowing MCP clients (Claude, custom agents) to discover and invoke Slack tools through a unified protocol interface.

Solves for

I want to integrate Slack into my MCP-compatible AI client without writing custom API wrappersI need my AI agent to discover available Slack capabilities at runtime via MCP tool introspectionI want to use the same Slack integration across multiple MCP clients (Claude, custom agents, etc.)

Best for

Developers building MCP-compatible AI agents that need Slack integration

Teams using Claude or other MCP clients that want standardized Slack access

Organizations standardizing on MCP for AI tool integration

Requires

Node.js 16+ (TypeScript SDK requirement)

MCP client that supports Tools primitive

Slack bot token (passed to server at startup or via environment variable)

Limitations

MCP protocol overhead adds ~50-100ms per tool invocation compared to direct API calls

Tool discovery is static at server startup; new capabilities require server restart

Error handling is limited to JSON-RPC error responses; no built-in retry logic

What makes it unique

Implements the full MCP server lifecycle (initialization, tool registration, request handling) using the official TypeScript SDK, making it a reference implementation for how to expose third-party APIs as MCP tools. The server handles protocol-level concerns (schema validation, error serialization) transparently, allowing clients to treat Slack as a native capability.

vs alternatives

More standardized than custom API wrappers because it uses the official MCP protocol; more discoverable than direct Slack SDK usage because tools are self-describing; enables multi-client reuse because MCP is client-agnostic.

slack authentication and token management via mcp context

Medium confidence

Manages Slack bot token authentication by accepting the token at server initialization (via environment variable or startup parameter) and using it for all subsequent API calls. The server stores the token securely in memory and passes it to the Slack SDK for each request, handling token validation and API authentication errors. Does not implement token refresh or rotation; assumes long-lived bot tokens.

Solves for

I need to securely pass my Slack bot token to the MCP server without exposing it in client codeI want the server to handle authentication so my MCP client doesn't need to know about tokensI need to validate that the token has required scopes before exposing Slack tools

Best for

Teams deploying MCP servers in controlled environments (internal servers, Docker containers)

Developers who want to separate authentication concerns from client code

Organizations using environment-based secret management (CI/CD, container orchestration)

Requires

Valid Slack bot token with required scopes (conversations:read, channels:history, chat:write, reactions:write)

Environment variable SLACK_BOT_TOKEN or command-line parameter at server startup

Network connectivity to Slack API (api.slack.com) over HTTPS

Limitations

Token is stored in server memory; no encryption at rest

No token refresh mechanism; long-lived tokens must be manually rotated

No scope validation at startup; invalid or insufficient scopes only fail when tools are invoked

What makes it unique

Implements authentication at the MCP server level rather than delegating to clients, centralizing token management and reducing the risk of token exposure in client code. The server acts as a trusted intermediary, validating all requests against the stored token.

vs alternatives

More secure than client-side token management because the token never leaves the server; simpler than OAuth flows because it uses long-lived bot tokens; more centralized than per-request authentication because the token is managed once at startup.

slack api error handling and resilience with mcp error responses

Medium confidence

Implements error handling for Slack API failures (rate limits, invalid channels, permission errors, network timeouts) by catching exceptions from the Slack SDK and translating them into JSON-RPC error responses. The server returns descriptive error messages to MCP clients, including error codes and context, enabling clients to implement retry logic or graceful degradation. Does not implement automatic retries or exponential backoff.

Solves for

I want my MCP client to receive clear error messages when a Slack operation failsI need to distinguish between recoverable errors (rate limits) and permanent failures (invalid channel)I want to implement client-side retry logic based on error codes returned by the server

Best for

AI agents that need to handle Slack API failures gracefully

Developers building resilient MCP clients with retry logic

Teams that need visibility into why Slack operations fail

Requires

MCP client that can parse JSON-RPC error responses

Slack bot token with appropriate scopes for the operation being attempted

Limitations

Error messages are limited to what Slack API returns; some errors lack detailed context

Rate limit errors (429) are not automatically retried; clients must implement backoff

Network timeouts are not distinguished from API errors; clients cannot differentiate transient vs permanent failures

What makes it unique

Translates Slack API errors into standardized JSON-RPC error responses, providing a consistent error interface across all tools. The server preserves Slack-specific error details in the error data field, allowing clients to implement sophisticated error handling without parsing error messages.

vs alternatives

More informative than silent failures because errors are explicitly returned; more standardized than raw Slack error responses because they conform to JSON-RPC; enables client-side retry logic because error codes are machine-readable.

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 Slack MCP Server, ranked by overlap. Discovered automatically through the match graph.

MCP Server29

@sigmacomputing/slack-mcp-server

MCP server for interacting with Slack

slack channel and conversation retrieval via mcp resourcesslack thread and reply managementslack message sending via mcp protocolslack user and workspace metadata lookup

4 shared capabilities

MCP Server31

@sigmacomputing/slack-mcp-server

MCP server for interacting with Slack

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

4 shared capabilities

MCP Server29

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 workspace message retrieval and search via mcpslack channel and user metadata exposure via mcp resourcesslack message posting and thread reply via mcp toolsthread-aware message context retrieval

4 shared capabilities

MCP Server28

slack-relay-mcp

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

mcp resource exposure for slack channels and messagescli-based slack message sending and retrievalmulti-workspace slack support with workspace routingslack message relay via mcp protocol

4 shared capabilities

MCP Server24

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 postingslack conversation history retrieval with context windowing

3 shared capabilities

MCP Server45

Slack

Slack is a channel-based messaging platform. With Slack, people can work together more effectively, connect all their software tools and services, and find the information they need to do their best work — all within a secure, enterprise-grade environment.

channel-based messaging

1 shared capability

Best For

✓AI agents and assistants that need workspace awareness before taking Slack actions
✓Teams building multi-channel notification systems with LLM orchestration
✓Developers integrating Slack into MCP-based AI workflows
✓AI assistants that need to read Slack conversation history before generating responses
✓Chatbots that require thread context to maintain conversation coherence
✓Analytics and monitoring agents that analyze Slack communication patterns
✓AI agents that need to communicate results or alerts back to Slack users
✓Chatbots that generate responses and post them to channels or threads

Known Limitations

⚠Pagination is automatic but large workspaces (10k+ channels) may incur multiple API calls with latency
⚠Returns only channels the bot token has permission to view; private channels require explicit membership
⚠No filtering on the server side — clients must filter results themselves
⚠Channel metadata is point-in-time; archived/unarchived status changes require re-querying
⚠API rate limits apply (typically 1 request per second per workspace); large history requests may require backoff
⚠Message content is limited to what Slack stores; deleted messages are not retrievable

Requirements

Slack workspace with bot user createdBot token with 'conversations:read' scopeMCP client that supports the Tools primitiveNetwork connectivity to Slack API (api.slack.com)Slack bot token with 'channels:history' and/or 'groups:history' scopesValid channel ID (not channel name)MCP client implementationOptional: thread timestamp for thread-specific retrieval

Input / Output

Accepts: none (tool takes no parameters), channel_id (string), limit (integer, optional, default 10), oldest (float timestamp, optional), latest (float timestamp, optional), thread_ts (float timestamp, optional, for thread replies), channel (string, channel ID), text (string, message content), reply_broadcast (boolean, optional, to share thread reply in channel), metadata (object, optional, for custom metadata fields), thread_ts (float timestamp, required, identifies the thread), text (string, reply message content), reply_broadcast (boolean, optional, default false, to share reply in channel), timestamp (float, message timestamp), emoji (string, emoji name without colons), JSON-RPC 2.0 requests with tool name and parameters, none (token is provided at server startup, not per-request), any tool invocation that may fail

Produces: JSON array of channel objects with id, name, is_member, is_private, is_archived, topic, purpose, created, num_members, JSON array of message objects with type, user, text, ts, thread_ts, reply_count, reply_users_count, latest_reply, JSON object with ok (boolean), channel (string), ts (string, message timestamp), message (object with full message details), JSON object with ok (boolean), channel (string), ts (string, reply message timestamp), thread_ts (string, parent thread timestamp), JSON object with ok (boolean), error (string, optional, if reaction failed), JSON-RPC 2.0 responses with tool result or error, none (authentication is implicit in all tool responses), JSON-RPC error response with code (integer), message (string), data (object with Slack error details)

UnfragileRank

Adoption70%(25% weight)

Quality85%(25% weight)

Ecosystem52%(15% weight)

Match Graph25%(30% weight)

Freshness100%(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

8 capabilities

Visit Slack MCP Server→

About

Official MCP server for Slack workspace integration. Exposes tools for listing channels, reading message history, posting messages, replying to threads, and managing reactions in Slack.

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Capabilities8 decomposed

slack workspace channel enumeration via mcp protocol

Medium confidence

Solves for

Best for

AI agents and assistants that need workspace awareness before taking Slack actions

Teams building multi-channel notification systems with LLM orchestration

Developers integrating Slack into MCP-based AI workflows

Requires

Slack workspace with bot user created

Bot token with 'conversations:read' scope

MCP client that supports the Tools primitive

Limitations

Pagination is automatic but large workspaces (10k+ channels) may incur multiple API calls with latency

Returns only channels the bot token has permission to view; private channels require explicit membership

No filtering on the server side — clients must filter results themselves

What makes it unique

vs alternatives

slack message history retrieval with thread context

Medium confidence

Solves for

Best for

AI assistants that need to read Slack conversation history before generating responses

Chatbots that require thread context to maintain conversation coherence

Analytics and monitoring agents that analyze Slack communication patterns

Requires

Slack bot token with 'channels:history' and/or 'groups:history' scopes

Valid channel ID (not channel name)

MCP client implementation

Limitations

API rate limits apply (typically 1 request per second per workspace); large history requests may require backoff

Message content is limited to what Slack stores; deleted messages are not retrievable

Thread replies require separate API call (replies.list), adding latency for deep thread context

What makes it unique

vs alternatives

More context-aware than simple message fetching because it supports thread-aware retrieval; more efficient than raw Slack API calls because the MCP server can batch and cache common queries.

slack message posting with formatting and metadata

Medium confidence

Solves for

Best for

AI agents that need to communicate results or alerts back to Slack users

Chatbots that generate responses and post them to channels or threads

Automation workflows that need to notify teams of events or decisions

Requires

Slack bot token with 'chat:write' scope

Valid channel ID (not channel name)

Message text content (plain text or Block Kit JSON)

Limitations

Message size is limited to 4000 characters for plain text; Block Kit payloads have separate size limits

Bot token must have 'chat:write' scope; cannot post to private channels without explicit membership

Formatting support depends on Slack client version; some Block Kit features may not render in older clients

What makes it unique

vs alternatives

More flexible than webhook-based posting because it supports threading, metadata, and dynamic formatting; more discoverable than raw API calls because the tool schema is self-describing in MCP.

slack thread reply composition with context awareness

Medium confidence

Solves for

Best for

Conversational AI agents that need to maintain thread-based discussions

Support bots that respond to user questions within existing threads

Multi-turn dialogue systems where context is organized by thread

Requires

Slack bot token with 'chat:write' scope

Valid channel ID

Valid thread_ts (message timestamp of the thread root)

Limitations

Thread timestamp (thread_ts) must be valid and correspond to an existing message; invalid timestamps fail silently

Broadcast replies (reply_broadcast=true) are visible in channel but may create notification fatigue

Thread replies cannot be edited via this tool; requires separate chat.update API

What makes it unique

vs alternatives

slack message reaction management (add/remove emoji reactions)

Medium confidence

Solves for

Best for

AI agents that need lightweight feedback mechanisms without posting messages

Chatbots that acknowledge user requests with emoji reactions

Automation workflows that mark messages as processed or reviewed

Requires

Slack bot token with 'reactions:write' scope

Valid channel ID

Valid message timestamp (ts)

Limitations

Emoji name must be valid Slack emoji (standard or custom workspace emoji); invalid names fail with error

Bot token must have 'reactions:write' scope; cannot add reactions to messages in channels the bot cannot access

Removing a reaction that doesn't exist returns success but has no effect

What makes it unique

vs alternatives

mcp protocol transport and tool schema exposition

Medium confidence

Solves for

Best for

Developers building MCP-compatible AI agents that need Slack integration

Teams using Claude or other MCP clients that want standardized Slack access

Organizations standardizing on MCP for AI tool integration

Requires

Node.js 16+ (TypeScript SDK requirement)

MCP client that supports Tools primitive

Slack bot token (passed to server at startup or via environment variable)

Limitations

MCP protocol overhead adds ~50-100ms per tool invocation compared to direct API calls

Tool discovery is static at server startup; new capabilities require server restart

Error handling is limited to JSON-RPC error responses; no built-in retry logic

What makes it unique

vs alternatives

slack authentication and token management via mcp context

Medium confidence

Solves for

Best for

Teams deploying MCP servers in controlled environments (internal servers, Docker containers)

Developers who want to separate authentication concerns from client code

Organizations using environment-based secret management (CI/CD, container orchestration)

Requires

Valid Slack bot token with required scopes (conversations:read, channels:history, chat:write, reactions:write)

Environment variable SLACK_BOT_TOKEN or command-line parameter at server startup

Network connectivity to Slack API (api.slack.com) over HTTPS

Limitations

Token is stored in server memory; no encryption at rest

No token refresh mechanism; long-lived tokens must be manually rotated

No scope validation at startup; invalid or insufficient scopes only fail when tools are invoked

What makes it unique

vs alternatives

slack api error handling and resilience with mcp error responses

Medium confidence

Solves for

Best for

AI agents that need to handle Slack API failures gracefully

Developers building resilient MCP clients with retry logic

Teams that need visibility into why Slack operations fail

Requires

MCP client that can parse JSON-RPC error responses

Slack bot token with appropriate scopes for the operation being attempted

Limitations

Error messages are limited to what Slack API returns; some errors lack detailed context

Rate limit errors (429) are not automatically retried; clients must implement backoff

Network timeouts are not distinguished from API errors; clients cannot differentiate transient vs permanent failures

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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Slack MCP Server

Capabilities8 decomposed

slack workspace channel enumeration via mcp protocol

slack message history retrieval with thread context

slack message posting with formatting and metadata

slack thread reply composition with context awareness

slack message reaction management (add/remove emoji reactions)

mcp protocol transport and tool schema exposition

slack authentication and token management via mcp context

slack api error handling and resilience with mcp error responses

Related Artifactssharing capabilities

@sigmacomputing/slack-mcp-server

@sigmacomputing/slack-mcp-server

slack-mcp-server

slack-relay-mcp

Slack

Slack

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

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Slack MCP Server

Capabilities8 decomposed

slack workspace channel enumeration via mcp protocol

slack message history retrieval with thread context

slack message posting with formatting and metadata

slack thread reply composition with context awareness

slack message reaction management (add/remove emoji reactions)

mcp protocol transport and tool schema exposition

slack authentication and token management via mcp context

slack api error handling and resilience with mcp error responses

Related Artifactssharing capabilities

@sigmacomputing/slack-mcp-server

@sigmacomputing/slack-mcp-server

slack-mcp-server

slack-relay-mcp

Slack

Slack

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

About

Categories

Alternatives to Slack MCP Server

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