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in2out

Mattermost S MCP

by in2out
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Server Quality Checklist

58%
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  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose with no overlap: list_webhooks retrieves information, send_message posts content, and set_default configures preferences. The descriptions clearly differentiate between monitoring, communication, and setup functions.

    Naming Consistency5/5

    All tools follow a consistent 'mattermost_verb_noun' pattern with snake_case throughout. The naming is predictable and uniform across the set, making it easy to understand the domain and action for each tool.

    Tool Count3/5

    With only 3 tools, the server feels thin for a Mattermost integration, as it lacks operations like updating or deleting webhooks, managing users, or handling other common chat platform features. However, it covers a basic workflow adequately.

    Completeness2/5

    The tool set is severely incomplete for a Mattermost server, missing essential CRUD operations such as creating, updating, or deleting webhooks, as well as broader functionality like user management, channel operations, or message editing. This will likely cause agent failures in more complex tasks.

  • Average 3/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

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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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool sends messages but lacks details on permissions, rate limits, error handling, or response format. This is inadequate for a mutation tool, as it doesn't inform the agent about potential side effects or operational constraints.

    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 a single, efficient sentence that gets straight to the point without unnecessary words. It's appropriately sized for the tool's complexity, though it could be slightly more structured (e.g., by explicitly noting optional parameters).

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

    Completeness2/5

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

    Given the tool's mutation nature, lack of annotations, and no output schema, the description is incomplete. It doesn't explain what happens after sending (e.g., success/failure response, message ID), how defaults work, or any behavioral nuances, leaving significant gaps for an AI agent to operate effectively.

    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% description coverage, so the schema already documents both parameters ('text' and 'channel'). The description adds minimal value by implying the 'channel' parameter is optional, but this is redundant with the schema's required field list. Baseline 3 is appropriate as the schema does the heavy lifting.

    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 clearly states the action ('send message') and resource ('via default or specified channel webhook'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'mattermost_list_webhooks' or 'mattermost_set_default', which prevents a perfect score.

    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 (e.g., 'mattermost_set_default' for setting defaults) or any prerequisites. It mentions a 'default or specified channel webhook' but doesn't clarify how defaults are set or when to specify a channel, leaving usage context vague.

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

  • Behavior2/5

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

    With no annotations provided, the description carries the full burden of behavioral disclosure. While '설정합니다' (sets) implies a mutation operation, the description doesn't disclose important behavioral traits like whether this requires admin permissions, whether it overwrites existing default webhook settings, what happens if the channel doesn't exist, or any rate limits. For a mutation tool with zero annotation coverage, this represents a significant gap in behavioral transparency.

    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, efficient sentence that gets straight to the point without any wasted words. It's appropriately sized for a single-parameter tool and front-loads the essential information about what the tool does.

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

    Completeness2/5

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

    For a mutation tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what happens after execution (success/failure indicators), doesn't mention permission requirements, and provides no information about the tool's behavior beyond the basic action. Given the complexity of a system configuration tool, more contextual information would be expected.

    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 schema description coverage is 100%, with the single parameter 'channel' well-documented in the schema as '기본으로 설정할 채널명' (channel name to set as default). The description doesn't add any meaningful parameter semantics beyond what the schema already provides, so it meets the baseline of 3 for high schema coverage situations.

    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 clearly states the action ('지정한 채널을...설정합니다' - sets the specified channel) and resource ('기본 웹훅' - default webhook), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like mattermost_list_webhooks or mattermost_send_message, which prevents a perfect score.

    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. There's no mention of prerequisites (e.g., needing admin permissions), when this should be used instead of other webhook-related tools, or any exclusions. It simply states what the tool does without contextual usage information.

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

  • Behavior2/5

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

    With no annotations provided, the description carries the full burden of behavioral disclosure. While '확인합니다' (check/verify) implies a read-only operation, the description doesn't explicitly state whether this requires authentication, what permissions are needed, how results are returned, or any rate limits. It provides minimal behavioral context beyond the basic action.

    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, efficient sentence in Korean that directly states the tool's purpose without any unnecessary words or structural complexity. It's appropriately sized for a simple list operation with no parameters.

    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 zero-parameter list operation with no output schema, the description adequately explains what the tool does. However, without annotations covering behavioral aspects like authentication requirements or response format, and with sibling tools that aren't differentiated, there are clear contextual gaps that prevent higher completeness.

    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 tool has 0 parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description appropriately doesn't discuss parameters, maintaining focus on the tool's purpose. This meets the baseline expectation for zero-parameter tools.

    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 clearly states the action ('확인합니다' - check/verify) and resource ('등록된 Mattermost 웹훅 채널 목록' - registered Mattermost webhook channel list), providing a specific verb+resource combination. However, it doesn't explicitly distinguish this from sibling tools like mattermost_send_message or mattermost_set_default, which prevents a perfect score.

    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 the sibling tools mattermost_send_message or mattermost_set_default. There's no mention of alternatives, prerequisites, or specific contexts where this tool is appropriate versus others.

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

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