Which integrations are available for this server?

Enables bidirectional Slack communication, allowing users to send notifications with varying urgency levels, ask questions and wait for replies via Slack threads, and manage channel messages.

How do I use Slack Notifier MCP?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Slack Notifier MCP notify me on Slack when the long-running tests are finished" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

Slack Notifier MCP

by Strand-AI

Overview Schema Related Servers Score Discussions

Python

Remote

Slack Notifier MCP

Python 3.10+ MCP License: MIT

MCP server for bidirectional Slack communication with Claude Code. Get notified when tasks complete, and respond to Claude's questions directly from Slack.

Quick Start

# Add to Claude Code (one command)
claude mcp add slack-notifier -s user \
  -e SLACK_BOT_TOKEN=xoxb-your-token \
  -e SLACK_DEFAULT_CHANNEL=YOUR-CHANNEL-ID \
  -- uvx slack-notifier-mcp@latest

Related MCP server: Slack Note Capture MCP Server

Features

Send Messages - Send messages with optional urgency levels and thread support
Ask & Wait - Ask questions and wait for replies via Slack threads
Bidirectional - Reply to Claude from Slack, get responses back in your terminal
Urgency Levels - Normal, important, and critical notifications with appropriate formatting

Slack App Setup

Before using this server, you need to create a Slack app:

Go to api.slack.com/apps and click Create New App
Choose From scratch, name it (e.g., "Claude Code"), and select your workspace
Go to OAuth & Permissions in the sidebar
Under Scopes > Bot Token Scopes, add:
- chat:write - Send messages
- channels:history - Read public channel messages
- groups:history - Read private channel messages
- im:history - Read DM messages
- users:read - Get user display names
Click Install to Workspace at the top
Copy the Bot User OAuth Token (starts with xoxb-)

To get your default channel ID:

Open Slack, right-click the channel, and select View channel details
At the bottom, copy the Channel ID (starts with C)

Installation

Claude Code (Recommended)

claude mcp add slack-notifier -s user \
  -e SLACK_BOT_TOKEN=xoxb-your-token \
  -e SLACK_DEFAULT_CHANNEL=YOUR-CHANNEL-ID \
  -- uvx slack-notifier-mcp@latest

VS Code

code --add-mcp '{"name":"slack-notifier","command":"uvx","args":["slack-notifier-mcp@latest"],"env":{"SLACK_BOT_TOKEN":"xoxb-your-token","SLACK_DEFAULT_CHANNEL":"YOUR-CHANNEL-ID"}}'

Other MCP Clients

Add to your Claude Desktop config:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
Linux: ~/.config/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "slack-notifier": {
      "command": "uvx",
      "args": ["slack-notifier-mcp@latest"],
      "env": {
        "SLACK_BOT_TOKEN": "xoxb-your-token",
        "SLACK_DEFAULT_CHANNEL": "YOUR-CHANNEL-ID"
      }
    }
  }
}

Go to Settings → MCP → Add new MCP Server
Select command type
Enter command: uvx slack-notifier-mcp@latest
Add environment variables for SLACK_BOT_TOKEN and SLACK_DEFAULT_CHANNEL

Or add to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "slack-notifier": {
      "command": "uvx",
      "args": ["slack-notifier-mcp@latest"],
      "env": {
        "SLACK_BOT_TOKEN": "xoxb-your-token",
        "SLACK_DEFAULT_CHANNEL": "YOUR-CHANNEL-ID"
      }
    }
  }
}

Any MCP-compatible client can use slack-notifier:

{
  "mcpServers": {
    "slack-notifier": {
      "command": "uvx",
      "args": ["slack-notifier-mcp@latest"],
      "env": {
        "SLACK_BOT_TOKEN": "xoxb-your-token",
        "SLACK_DEFAULT_CHANNEL": "YOUR-CHANNEL-ID"
      }
    }
  }
}

Local Development

git clone https://github.com/strand-ai/slack-notifier-mcp.git
cd slack-notifier-mcp
uv sync
uv run slack-notifier-mcp

MCP Tools

`send`

Send a message to Slack with optional urgency and thread support.

# Simple message
send(message="Build completed successfully")

# With urgency (adds formatting and @here for critical)
send(
    message="Server is down!",
    urgency="critical"  # or "normal", "important"
)

# Reply in a thread
send(
    message="Done with the first step, moving on...",
    thread_ts="1234567890.123456"
)

# Mention user
send(
    message="Need your attention",
    mention_user=True
)

Parameters:

message (required): Message text (supports Slack mrkdwn)
channel (optional): Channel ID or name (uses default if not set)
thread_ts (optional): Thread timestamp to reply in a thread
urgency (optional): normal, important, or critical
mention_user (optional): If true, @mentions the configured user

`ask_user`

Send a question and wait for the user's reply.

ask_user(
    question="Should I use PostgreSQL or SQLite for the database?",
    context="Setting up the backend for the new API",
    timeout_minutes=10
)
# Returns: {"success": True, "reply": "Use PostgreSQL", ...}

Parameters:

question (required): The question to ask
channel (optional): Channel ID or name
context (optional): Additional context about what you're working on
timeout_minutes (optional): How long to wait (default 5, max 30)

`get_thread_replies`

Check for new replies in a thread.

get_thread_replies(
    channel="YOUR-CHANNEL-ID",
    thread_ts="1234567890.123456",
    since_ts="1234567891.000000"  # Only newer messages
)

Environment Variables

Variable	Required	Description
`SLACK_BOT_TOKEN`	Yes	Bot token from Slack app (xoxb-...)
`SLACK_DEFAULT_CHANNEL`	No	Default channel for notifications

Example Usage

Tell Claude Code:

"Notify me on Slack when the tests finish running"

"Ask me on Slack whether to proceed with the database migration"

"Send a Slack notification if any errors occur while I'm away"

Debugging

Run the MCP inspector to test tools:

npx @anthropics/mcp-inspector uvx slack-notifier-mcp@latest

Check if your token works:

curl -H "Authorization: Bearer xoxb-your-token" \
  https://slack.com/api/auth.test

Development

# Install with dev dependencies
uv sync --extra dev

# Run tests
uv run pytest

# Format code
uv run black slack_mcp
uv run ruff check slack_mcp --fix

License

MIT

Available Tools

3 tools

ask_userA

Send a question to the user via Slack and wait for their reply.

Use this when you need user input or a decision. The user will be notified and can reply in the Slack thread. This will BLOCK until the user replies or the timeout is reached.

IMPORTANT - NON-BLOCKING USAGE: To avoid blocking, run this tool in a background agent/task. Example with Claude Code's Task tool:

Task(
    prompt="Call ask_user with question='Your question here'",
    run_in_background=True
)

This lets you continue working while waiting for the Slack reply. You'll be notified when the background task completes with the user's response.

Args: question: The question to ask the user. channel: Channel name or ID. Uses SLACK_DEFAULT_CHANNEL if not specified. context: Optional context to include (e.g., what you're working on). timeout_minutes: How long to wait for a reply (default 5 minutes, max 30).

Returns: Dict with success status and user's reply text if received.

ParametersJSON Schema

Name	Required	Description	Default
`question`	Yes
`channel`	No
`context`	No
`timeout_minutes`	No

Output Schema

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

A4.7/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so the description carries full burden. It clearly states that the tool blocks until reply or timeout, explains the return dict, and gives a non-blocking alternative. All behavioral traits are disclosed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with sections and front-loaded purpose. The code example adds value but lengthens it slightly. Overall efficient for the complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 4 parameters, blocking behavior, and an output schema (mentioned but not detailed), the description covers all essential aspects: usage, blocking, timeout, non-blocking alternative, default channel, and return value.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description adds detailed meaning for all parameters: question, channel (default SLACK_DEFAULT_CHANNEL), context, and timeout_minutes (default 5, max 30). This fully compensates for the schema's lack of descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Send a question to the user via Slack') and the resource ('user via Slack'), and it distinguishes itself from siblings like 'send' and 'get_thread_replies' by highlighting the blocking wait for reply.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'Use this when you need user input or a decision' and provides a non-blocking usage pattern. It doesn't explicitly list when not to use, but the blocking behavior is clearly stated, giving enough guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_thread_repliesA

Get replies in a Slack thread.

Use this to check for new messages in a thread you started.

Args: channel: Channel ID containing the thread. thread_ts: Timestamp of the parent message. since_ts: Only return messages after this timestamp (optional).

Returns: Dict with success status and list of replies.

ParametersJSON Schema

Name	Required	Description	Default
`channel`	Yes
`thread_ts`	Yes
`since_ts`	No

Output Schema

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

A3.8/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must disclose behavior. It explains the return format (dict with success status and list of replies) and the optional since_ts parameter. However, it does not mention potential errors, rate limits, or if the tool requires authentication.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is structured with an Args section and Returns section, making it easy to parse. It is concise without unnecessary elaboration, though the first sentence 'Get replies in a Slack thread.' is somewhat redundant with the name.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 3 parameters and an output schema mentioned but not detailed, the description provides adequate information for basic usage. However, it omits details about error handling, pagination of replies, and behavior if the thread is not found, leaving gaps for complex usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It explains each parameter: channel is a 'Channel ID', thread_ts is a 'Timestamp of the parent message', and since_ts is 'optional' and 'only return messages after this timestamp'. This adds sufficient meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool gets replies in a Slack thread, using specific verb 'Get' and resource 'replies'. It distinguishes from sibling tools 'ask_user' and 'send' which have different purposes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description suggests using the tool 'to check for new messages in a thread you started', providing a specific use case. However, it lacks explicit guidance on when not to use it or alternatives, such as using the 'send' tool for posting messages.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

sendA

Send a message to a Slack channel or thread.

Args: message: Message text. Supports Slack mrkdwn formatting. channel: Channel name or ID. Uses SLACK_DEFAULT_CHANNEL if not specified. thread_ts: Thread timestamp to reply in a thread. urgency: Message urgency level. 'critical' adds @here mention. mention_user: If True, @mentions the configured user (requires SLACK_USER_ID).

Returns: Dict with success status and message details.

ParametersJSON Schema

Name	Required	Default
`message`	Yes
`channel`	No
`thread_ts`	No
`urgency`	No	normal
`mention_user`	No

Output Schema

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

A4.3/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It explains message formatting (mrkdwn), channel default, thread replies, urgency effects (@here), and mention requirement (SLACK_USER_ID). However, it omits potential side effects, rate limits, or error conditions, so it is adequate but not fully transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise (two paragraphs) with a clear 'Args' and 'Returns' structure. Every sentence adds value, starting with a direct purpose statement. No redundant or vague phrases.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 5 parameters and an output schema, the description covers all parameters and the return type. It addresses common usage scenarios but lacks details on error responses or prerequisites (e.g., Slack permissions). Still, it is mostly complete for typical operation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description compensates fully by explaining each parameter: message (mrkdwn), channel (default, name/ID), thread_ts (timing), urgency (enum with @here), and mention_user (boolean with config requirement). It adds meaning beyond the schema's type/enum constraints.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Send a message to a Slack channel or thread.', specifying the action and the target resource. It is distinct from sibling tools 'ask_user' (likely for questioning) and 'get_thread_replies' (fetching responses), so the agent can easily differentiate when to use this tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context on when to use specific parameters like 'thread_ts' for replying and 'urgency' for priority. It also mentions default channel and @mentions. Although it doesn't explicitly state 'when not to use' or compare to siblings, the purpose and parameter guidance are clear enough for most use cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

3 tool updatesv0.3.0Jan 31, 2026
- First observedask_user
- First observedget_thread_replies
- First observedsend

Install Server

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

A4/5.0

Disambiguation5/5

Each tool has a distinct purpose: ask_user for interactive questions, get_thread_replies for retrieving thread responses, and send for posting messages. No semantic overlap.

Naming Consistency4/5

All tools use snake_case verb_noun pattern (ask_user, get_thread_replies), with 'send' being a single-verb exception but still follows the verb-first convention. Minor inconsistency in specificity.

Tool Count3/5

Three tools is minimal for a Slack integration, but the server's 'notifier' scope justifies a lean set. Still, the surface feels thin compared to typical Slack API needs.

Completeness3/5

Core messaging workflows are covered: send, read replies, and ask for input. However, missing essential operations like listing channels, updating messages, or managing reactions limit the surface.

Maintenance

ActivityInactive

ResponsivenessSyncing

Resources

GitHub Repository

Need Help?

Reddit Discussion

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