Skip to main content
Glama

Server Quality Checklist

50%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose targeting specific resources and actions: three tools for comments (add, delete, update), two for tasks (get, list), and one for listing comments. No overlap or ambiguity exists between these functions.

    Naming Consistency5/5

    All tools follow a consistent 'dooray_verb_noun' pattern with snake_case, using clear verbs like add, delete, get, list, and update. This uniformity makes the tool set predictable and easy to understand.

    Tool Count5/5

    With 6 tools, this server is well-scoped for managing tasks and comments in Dooray. Each tool serves a distinct and necessary function, avoiding bloat while covering core operations effectively.

    Completeness4/5

    The server provides complete CRUD coverage for comments (add, delete, update, list) and good task management (get, list), but lacks task creation, update, or deletion tools. This minor gap may require workarounds for full task lifecycle management.

  • Average 2.8/5 across 6 of 6 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
  • Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.

    If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.

    MCP servers without a LICENSE cannot be installed.

  • 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 states this is a read operation ('Get'), but doesn't cover aspects like authentication requirements, rate limits, error handling, or what 'detailed information' includes. For a tool with zero annotation coverage, this leaves significant behavioral gaps unaddressed.

    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, straightforward sentence that efficiently states the core function without unnecessary words. It's appropriately sized for a basic tool description, though it could be more front-loaded with additional context. There's no wasted language, making it concise.

    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?

    Given the tool's moderate complexity (2 required parameters, no annotations, but with an output schema), the description is minimally adequate. The output schema existence means return values don't need explanation in the description, but the lack of parameter semantics and behavioral context leaves gaps. It meets a bare minimum but doesn't fully address the tool's needs.

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

    Parameters2/5

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

    Schema description coverage is 0%, so the schema provides no parameter descriptions. The tool description doesn't mention parameters at all, failing to compensate for the schema gap. With 2 required parameters (project_id and post_id) that are undocumented in both schema and description, users lack essential context about what these IDs represent or how to obtain them.

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

    Purpose3/5

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

    The description states the action ('Get detailed information') and resource ('about a specific task'), which provides a basic understanding of purpose. However, it doesn't differentiate this tool from sibling tools like 'dooray_list_tasks' or explain what constitutes 'detailed information' versus what other tools might provide. The purpose is clear but lacks specificity and sibling differentiation.

    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 like 'dooray_list_tasks' or how it relates to sibling comment tools. There's no mention of prerequisites, context for selecting this tool, or exclusions. Usage is implied only by the tool name and basic description, with no explicit guidelines.

    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. It states the action is 'Delete' but doesn't clarify if this is permanent, reversible, requires specific user permissions, or has side effects like notifications. This leaves significant gaps in understanding the tool's behavior.

    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 no unnecessary words, making it highly efficient and front-loaded. It immediately conveys the core action without any fluff, earning full marks for conciseness.

    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 destructive nature (deletion), no annotations, 0% schema coverage, and the presence of an output schema (which might help but isn't described), the description is inadequate. It doesn't address critical aspects like permissions, reversibility, or parameter meanings, leaving the agent poorly equipped to use this tool correctly.

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

    Parameters2/5

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

    The schema description coverage is 0%, meaning none of the three parameters (project_id, post_id, log_id) are documented in the schema. The description adds no information about what these IDs represent, how to obtain them, or their format, failing to compensate for the schema's lack of documentation.

    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 ('Delete') and the resource ('a comment from a task'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'dooray_update_comment' or specify if it's permanent versus soft deletion, 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 like 'dooray_update_comment' for editing comments or 'dooray_list_comments' for viewing. It lacks context about prerequisites, permissions, or error conditions, offering minimal usage direction.

    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. It states the action is to 'Add a new comment,' which implies a write/mutation operation, but it doesn't disclose any behavioral traits such as required permissions, whether the operation is idempotent, rate limits, or what happens on failure. This leaves significant gaps for an agent to understand how to use it safely and effectively.

    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, clear sentence with no wasted words. It is appropriately sized and front-loaded, directly stating the tool's purpose without unnecessary elaboration.

    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?

    Given the tool has an output schema (which should cover return values), the description's minimalism is somewhat acceptable. However, as a mutation tool with no annotations and 0% schema description coverage, it lacks crucial context like error handling or side effects. The presence of an output schema raises the baseline, but the description still falls short of being fully complete.

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

    Parameters2/5

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

    The schema description coverage is 0%, meaning none of the three parameters (project_id, post_id, content) are documented in the schema. The description does not add any meaning beyond the parameter names, such as explaining what 'project_id' and 'post_id' refer to or any constraints on 'content.' This fails to compensate for the low 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 clearly states the action ('Add a new comment') and the target resource ('to a task'), which provides a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'dooray_update_comment' or 'dooray_list_comments', which would be needed for 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 are no mentions of prerequisites (like needing a valid project_id and post_id), exclusions, or comparisons to sibling tools such as 'dooray_update_comment' for modifying existing comments.

    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 full burden but only states the basic action without behavioral details. It doesn't disclose if this is a read-only operation, requires authentication, has rate limits, returns paginated results, or what happens with invalid inputs, leaving significant gaps for agent understanding.

    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, clear sentence with zero waste, making it highly concise and front-loaded. Every word contributes directly to stating the tool's purpose without unnecessary elaboration.

    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?

    Given the tool's moderate complexity (2 required parameters) and the presence of an output schema (which handles return values), the description is minimally adequate. However, with no annotations and low schema coverage, it lacks behavioral and parameter context, making it incomplete for safe agent use.

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

    Parameters2/5

    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 but adds no parameter semantics. It mentions 'a specific task' but doesn't explain what 'project_id' and 'post_id' represent, their formats, or how they relate to tasks, failing to bridge the schema gap.

    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 ('List') and resource ('comments on a specific task'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'dooray_get_task' or 'dooray_list_tasks' which might also involve task-related operations, leaving room for ambiguity in sibling context.

    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. It doesn't mention prerequisites (e.g., needing a valid project and post ID), exclusions, or comparisons to siblings like 'dooray_get_task' for task details or 'dooray_list_tasks' for broader listings.

    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 full burden for behavioral disclosure. It states this is a list operation but doesn't describe pagination behavior (though 'page' and 'size' parameters suggest it), rate limits, authentication needs, or what happens with invalid filters. The mention of 'optional filtering' is minimal behavioral context.

    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 with zero wasted words. It's appropriately sized for a list operation and front-loads the core purpose. Every word earns its place.

    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?

    Given the tool has 9 parameters with 0% schema coverage and no annotations, the description is incomplete—it doesn't explain filtering options or behavioral details. However, the presence of an output schema reduces the need to describe return values, making it minimally adequate but with clear gaps.

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

    Parameters2/5

    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 for 9 undocumented parameters. It only mentions 'optional filtering' generically without explaining what filters are available (workflow_class, to_member_ids, etc.) or their semantics. This adds minimal value beyond the parameter names in the schema.

    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 verb ('List') and resource ('tasks from Dooray project'), providing a specific purpose. However, it doesn't differentiate from sibling tools like 'dooray_get_task' (singular vs. plural) or 'dooray_list_comments' (tasks vs. comments), 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 mentions 'optional filtering' which implies some usage context, but provides no explicit guidance on when to use this tool versus alternatives like 'dooray_get_task' for single tasks or 'dooray_list_comments' for comments. No prerequisites or exclusions are mentioned.

    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?

    No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Update an existing comment' implies a mutation operation, but it doesn't disclose any behavioral traits such as permissions required, whether the update is reversible, rate limits, or what the response contains. For a mutation tool with zero annotation coverage, this is a significant gap in 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 with zero waste. It's front-loaded with the core action ('update') and resource ('comment'), making it immediately clear. Every word earns its place, and there's no unnecessary elaboration or redundancy.

    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?

    Given the tool has an output schema (which handles return values), the description's minimalism is somewhat acceptable. However, as a mutation tool with no annotations and 4 undocumented parameters, the description should do more to explain behavior and parameter usage. It's barely adequate for a basic update operation but leaves significant gaps in understanding how to use it effectively.

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

    Parameters2/5

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

    Schema description coverage is 0%, meaning none of the 4 parameters have descriptions in the schema. The description adds no information about parameters beyond what the schema provides (just titles like 'Project Id'). It doesn't explain what 'log_id' represents, how 'content' should be formatted, or the relationships between 'project_id', 'post_id', and 'log_id'. The description fails to compensate for the low 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 clearly states the verb ('update') and resource ('an existing comment'), making the purpose immediately understandable. It distinguishes from siblings like 'dooray_add_comment' (create) and 'dooray_delete_comment' (delete), though it doesn't explicitly mention these distinctions. The description is specific enough to understand what the tool does without being tautological.

    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. It doesn't mention prerequisites (e.g., needing an existing comment ID), exclusions, or comparisons to sibling tools like 'dooray_add_comment' for new comments or 'dooray_list_comments' for viewing. The agent must infer usage from the tool name and context alone.

    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

dooray-mcp MCP server

Copy to your README.md:

Score Badge

dooray-mcp 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/kwanok/dooray-mcp'

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