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izzzzzi

codewiki-mcp

by izzzzzi
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TypeScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.1.1

  • Disambiguation5/5

    Each tool has a clearly distinct purpose with no overlap: 'ask_repo' handles natural-language queries, 'fetch_repo' retrieves wiki content, and 'search_repos' finds indexed repositories. The descriptions make it easy to differentiate between querying, fetching, and searching functions.

    Naming Consistency5/5

    All tools follow a perfect 'codewiki_verb_noun' pattern with consistent snake_case formatting. The prefix 'codewiki_' is uniformly applied, and verbs ('ask', 'fetch', 'search') are distinct and appropriately paired with nouns ('repo' or 'repos').

    Tool Count3/5

    With only 3 tools, the set feels thin for a server focused on repository wiki interactions. While the tools cover basic operations, the scope might benefit from additional tools for updates, deletions, or more granular queries to handle common workflows more comprehensively.

    Completeness4/5

    The tools provide good coverage for core operations: searching repositories, fetching content, and asking questions. However, there are minor gaps such as lacking update or deletion tools for wiki content, which could limit agent capabilities in full lifecycle management scenarios.

  • Average 2.8/5 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
    • 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 MIT License.

  • 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.

  • This repository includes a glama.json configuration file.

  • 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.

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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 but offers minimal information. It implies a query operation but doesn't describe response format, error handling, rate limits, authentication needs, or whether it's read-only or mutative. For a tool with three parameters and no structured safety hints, 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 that directly states the tool's function without unnecessary words. It's appropriately sized and front-loaded, with every part contributing to understanding the core purpose, making it highly concise and well-structured.

    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 (three parameters, no output schema, no annotations), the description is incomplete. It doesn't cover parameter semantics, behavioral traits, or output expectations, leaving the agent with insufficient context to use the tool effectively beyond a basic understanding of its purpose.

    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 fails to do so. It doesn't explain the meaning or usage of 'repo', 'question', or 'history' parameters beyond their names. The description adds no semantic value beyond what's inferable from parameter names, leaving key details like repository format or history structure undocumented.

    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 ('Ask a natural-language question') and the target resource ('about a repository indexed in codewiki.google'), which distinguishes it from sibling tools like 'codewiki_fetch_repo' and 'codewiki_search_repos' that likely perform different operations. However, it doesn't specify what kind of information can be asked about (e.g., code, documentation, structure), making it slightly less specific than 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 'codewiki_fetch_repo' or 'codewiki_search_repos'. It doesn't mention prerequisites (e.g., the repository must be indexed), exclusions, or contextual cues for selection, leaving the agent to infer usage based on tool names alone.

    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 only states the basic action ('Search repositories') without details on permissions, rate limits, response format, or error handling. For a search 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 that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, making it easy to parse quickly.

    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 operation with 2 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits, parameter meanings, and expected outputs, making it insufficient for an agent to use the tool effectively without additional context.

    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 parameters 'query' and 'limit' are undocumented in the schema. The description adds no information about what 'query' should contain (e.g., search terms, filters) or how 'limit' affects results, failing to compensate for the coverage 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 verb ('Search') and resource ('repositories indexed by codewiki.google'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like codewiki_ask_repo or codewiki_fetch_repo, which likely have different purposes (e.g., querying vs. fetching specific repos).

    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?

    No guidance is provided on when to use this tool versus alternatives. The description doesn't mention sibling tools or contexts where this search function is preferred over other repository-related operations, leaving the agent without 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 mentions fetching content but doesn't cover critical aspects like authentication needs, rate limits, error handling, or the format of returned content. 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, efficient sentence that directly states the tool's function without unnecessary words. It is front-loaded with the core action and resource, making it highly concise and well-structured.

    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 (2 parameters, no annotations, no output schema), the description is incomplete. It fails to address key contextual elements like what the output looks like, how errors are handled, or prerequisites for use, making it inadequate for a tool that fetches content without structured support.

    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 description adds no parameter semantics beyond the input schema, which has 0% description coverage. It doesn't explain what 'repo' represents (e.g., repository name or URL) or the difference between 'aggregate' and 'pages' modes. However, with two parameters and no output schema, the baseline is 3 as the description doesn't compensate for the schema's lack of details.

    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 ('Fetch') and resource ('generated wiki content for a repository from codewiki.google'), making the purpose evident. However, it doesn't differentiate from sibling tools like codewiki_ask_repo or codewiki_search_repos, which likely have different functions (e.g., querying vs. searching).

    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?

    No guidance is provided on when to use this tool versus alternatives. The description lacks context about scenarios where fetching wiki content is appropriate compared to asking questions about the repo or searching for repos, leaving the agent without usage direction.

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

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