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cheesecrust

Confluence MCP Server

by cheesecrust
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Server Quality Checklist

50%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one retrieves a specific page by ID, while the other searches for pages by keyword using CQL. There is no overlap in functionality, making it easy for an agent to choose the correct tool based on whether it needs to fetch a known page or find pages matching a query.

    Naming Consistency5/5

    Both tools follow a consistent 'confluence_verb_noun' pattern (confluence_get_page, confluence_search), using snake_case and starting with the domain prefix. This predictable naming scheme enhances readability and reduces cognitive load for agents.

    Tool Count2/5

    With only 2 tools, the server feels severely under-scoped for a Confluence integration. A typical content management system like Confluence would require CRUD operations (create, update, delete pages), management of spaces or attachments, and more advanced querying. This minimal set limits agent capabilities significantly.

    Completeness2/5

    The toolset is highly incomplete for a Confluence server. While it covers basic retrieval and search, it lacks essential operations such as creating, updating, or deleting pages, managing comments or attachments, and handling spaces. This creates significant gaps that will cause agent failures in common workflows.

  • Average 2.9/5 across 2 of 2 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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  • This repository includes a README.md file.

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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?

    No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool fetches and converts HTML to text, implying a read-only operation, but does not cover critical aspects like authentication requirements, rate limits, error handling, or output format (e.g., structured text). For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

    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 directly states the tool's core function and key transformation (HTML to text). It is front-loaded with the main purpose and avoids unnecessary details. However, it could be slightly more structured by explicitly naming parameters or usage scenarios, but it remains concise and to the point.

    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 complexity (fetching and converting content), lack of annotations, and no output schema, the description is incomplete. It does not explain the return value (e.g., text format, potential truncation with 'maxChars'), error conditions, or dependencies like authentication. For a tool with these gaps, the description should provide more context to guide effective use.

    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?

    Schema description coverage is 100%, with clear documentation for both parameters: 'pageId' (Confluence page id) and 'maxChars' (본문 최대 길이, maximum length of body). The description adds minimal value beyond the schema, mentioning 'pageId' implicitly but not elaborating on parameter usage or constraints. With high schema coverage, the baseline score of 3 is appropriate as the description does not significantly enhance parameter understanding.

    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 tool's purpose: 'Confluence 페이지 ID로 본문을 가져옵니다' (fetches page content by Confluence page ID) with the additional detail 'HTML을 텍스트로 변환' (converts HTML to text). This specifies the verb (fetch), resource (page content), and a key transformation (HTML to text). It distinguishes from the sibling 'confluence_search' by focusing on retrieval by ID rather than search functionality.

    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 'confluence_search'. It mentions the input parameter 'pageId' but does not explain prerequisites (e.g., needing a valid page ID) or exclusions (e.g., not for searching). Without explicit usage context or comparisons, the agent must infer when this tool is appropriate.

    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. It mentions using CQL for searching, which adds some context, but it doesn't describe key behaviors such as authentication requirements, rate limits, pagination, or the format of search results. For a search tool with zero annotation coverage, this leaves significant gaps in understanding how the tool operates.

    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 directly states the tool's function without unnecessary words. It's appropriately sized and front-loaded, making it easy to understand at a glance.

    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 complexity of a search tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits, result formatting, and usage context. While the schema covers parameters well, the overall description doesn't provide enough information for an agent to fully understand how to invoke and interpret the tool's behavior.

    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?

    Schema description coverage is 100%, meaning the input schema fully documents both parameters ('query' and 'limit') with descriptions and constraints. The description adds no additional parameter information beyond what's in the schema, so it meets the baseline of 3 for high schema coverage without compensating value.

    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 tool's purpose: 'Confluence에서 키워드로 페이지를 검색합니다 (CQL 사용)' translates to 'Search for pages by keyword in Confluence (using CQL).' This specifies the verb (search), resource (pages), and method (CQL). However, it doesn't explicitly differentiate from the sibling tool 'confluence_get_page', which likely retrieves a specific page rather than searching, so it misses full sibling distinction.

    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 the sibling tool 'confluence_get_page' or any other search methods, nor does it specify prerequisites or exclusions. Usage is implied by the action but not explicitly stated.

    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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