Skip to main content
Glama
rokej

Slack MCP Server

by rokej

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.0

  • Disambiguation3/5

    The three tools are all variations of sending messages to Slack, which creates some overlap. send_payload and send_message especially could be confused, though send_markdown is clearly distinct. The descriptions help clarify input format differences, but the boundaries are not fully crisp.

    Naming Consistency5/5

    All tool names follow a consistent send_verb_noun pattern: send_payload, send_markdown, send_message. This makes the set predictable and easy to navigate.

    Tool Count5/5

    With only 3 tools, the server is tightly scoped to its purpose of sending Slack messages via webhook. Each tool covers a distinct input format, and there are no redundant or unnecessary tools.

    Completeness5/5

    For the stated domain of sending Slack messages via incoming webhooks, the server covers all major input formats: raw payload, markdown, and plain message. There are no obvious gaps for this narrow scope, though full Slack API features like reading messages are intentionally excluded.

  • Average 4/5 across 3 of 3 tools scored. Lowest: 3.1/5.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 1 commit in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing
  • This repository is licensed under Apache 2.0.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

  • Add a glama.json file to provide metadata about your server.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
      "$schema": "https://glama.ai/mcp/schemas/server.json",
      "maintainers": [
        "your-github-username"
      ]
    }

    Then . Browse examples.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior2/5

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

    No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the action ('Post') but does not mention side effects, response format, authentication requirements, or any error conditions. This is a significant gap for a write operation.

    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 a single, direct sentence with zero fluff or redundancy. It is appropriately concise and front-loaded, though it sacrifices context for brevity.

    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?

    With two well-documented parameters and an output schema present, the description is minimally viable. However, it lacks usage guidance and behavioral context (e.g., when to use this over siblings, what the response contains). The complexity is low, so the missing details represent clear but not fatal gaps.

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

    Parameters3/5

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

    The input schema already provides comprehensive descriptions for both parameters (text and blocks) with 100% coverage. The description adds no additional parameter semantics, so it does not exceed the baseline established for high schema coverage.

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

    Purpose4/5

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

    The description states a specific verb ('Post') and resource ('Slack message'), and mentions the method ('via Incoming Webhook'). It clearly conveys the tool's primary function, but does not differentiate it from sibling tools like send_payload or send_markdown.

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

    Usage Guidelines2/5

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

    The description provides no guidance on when to use this tool versus alternatives. With sibling tools present, the lack of any usage context or exclusions leaves the agent to guess based solely on the tool name.

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

  • Behavior5/5

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

    With no annotations provided, the description takes full responsibility for behavioral disclosure. It details specific edge-case handling: 'tables (bullets when links are present), mrkdwn inline formatting, Slack size limits, and multi-part splitting with (n/m) sequence headers.' This goes beyond a generic description and informs the agent of non-obvious transformations and constraints.

    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 two sentences, front-loaded with the core purpose and followed by a compact list of key behaviors. Every word earns its place, clearly conveying both the primary action and critical edge cases without unnecessary detail.

    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's complexity (Markdown conversion, Slack limits, multi-part splitting), the description covers essential behaviors and edge cases. An output schema exists, so return values are not required. However, it does not mention failure modes or webhook configuration prerequisites, which would make it fully complete.

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

    Parameters3/5

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

    The input schema has 100% parameter coverage, so the baseline is 3. The description does not describe individual parameters, but the schema already provides accurate descriptions. The Markdown-related behavior (e.g., multi-part splitting) enriches the meaning of the main 'markdown' parameter, but no additional semantics are needed for the others.

    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's function: 'Convert Markdown to Slack Block Kit and send via Incoming Webhook.' It identifies the specific verb (convert/send), the resource (Markdown to Slack Block Kit), and distinguishes from siblings by focusing on Markdown preprocessing, unlike send_payload or send_message.

    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 states the tool's input format ('Convert Markdown') and lists supported Markdown features, making it evident when to use this tool. It does not explicitly mention exclusions or alternative tools, but the purpose is clear enough to guide selection.

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

  • Behavior4/5

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

    With no annotations, the description carries the burden of disclosing behavior. It covers array handling (multi-part with 1s spacing) and 429 retry, referencing a known contract. It does not mention return values, but an output schema exists. This is meaningful behavioral context beyond the schema.

    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 two sentences, front-loaded with the core action, and includes only relevant behavioral details. No fluff or redundancy, making it highly scannable for an agent.

    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's low complexity (one parameter, output schema present), the description provides sufficient context: input format, array behavior, spacing, and retry. It doesn't explicitly explain return behavior, but that's covered by the output schema. Sibling differentiation is slightly implicit but adequate.

    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?

    The schema already provides 100% coverage for the payload parameter (object, array, or string). The description adds semantic value by clarifying that an array represents multi-part messages with spacing and retry, which is not evident from the schema alone. The string option isn't mentioned in the description but is covered by 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 action ('Post a pre-built Slack webhook payload') and the accepted input format (object or array). The reference to send_to_slack.sh and the sibling tool names (send_markdown, send_message) help distinguish this tool from those, as it focuses on raw payloads rather than formatted markdown or simple messages.

    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 implies usage for raw, pre-built payloads and explicitly describes the behavior for arrays (multi-part messages). It doesn't explicitly state when to use this over siblings, but the phrase 'pre-built' and the array semantics provide clear context. A direct comparison to alternatives would make it stronger.

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

GitHub Badge

Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

slack-mcp-server MCP server

Copy to your README.md:

Score Badge

slack-mcp-server MCP server

Copy to your README.md:

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/rokej/slack-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server