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gbrlpzz

zig-docs-mcp

by gbrlpzz

Server Quality Checklist

67%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool targets a distinct purpose: version checking, updating, language reference, standard library docs, changelog, performance guidance, and a unified search that complements the others. No two tools appear to do the same thing, and descriptions clarify boundaries.

    Naming Consistency4/5

    Most tools follow a 'zig_' prefix, but the second element varies in style (noun, verb_noun, abbreviation). 'perf_guidance' breaks the prefix pattern. Still, names are short, descriptive, and predictable enough for an agent to infer purpose.

    Tool Count5/5

    Seven tools is well-scoped for a documentation and toolchain server. Each tool earns its place, covering version checks, updates, references, and search, without bloat or missing essentials.

    Completeness5/5

    The surface covers the core documentation lifecycle: version status, update, language reference, std docs, changelog, performance guidance, and a cross-cutting search. There are no obvious gaps for the stated purpose of providing Zig documentation and version management.

  • Average 3.7/5 across 7 of 7 tools scored. Lowest: 2.8/5.

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

    • No community issues in the last 6 months
    • 2 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
  • 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.

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  • 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?

    With no annotations, the description must fully disclose behavioral traits. It only states the output ('release-notes digest') but not whether the operation is read-only, whether it makes network calls, whether the 'force' parameter triggers a refresh, or if there are any side effects. This minimal disclosure leaves significant ambiguity for a fetch-style tool.

    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, concise sentence that is front-loaded with the core purpose. It is efficient and easy to parse. However, it omits parameter information, making it less complete though still appropriately sized for the tool's simplicity.

    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 two optional parameters and an output schema, the description should explain what both parameters do and when to set them. It does neither. The output schema exists, so return format is covered, but the parameter semantics are entirely missing. The tool is simple, yet the description fails to equip the agent to use it correctly.

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

    Parameters1/5

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

    The input schema has two parameters (force, channel) but neither has a description, and the schema coverage is 0%. The description does not mention these parameters at all, so the agent has no explanation of what 'force' or 'channel' control. This is a critical gap for a tool with optional parameters.

    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 purpose: it provides a digest of release notes for the current version of a given channel. The phrase 'what changed' conveys the specific information returned. This distinguishes it from sibling tools like zig_version_status (version info), zig_update (update action), and zig_search (search).

    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?

    There is no guidance on when to use this tool versus alternatives. It does not mention any situational context, such as 'use this to see recent changes' or 'for details on a specific version use zig_search'. No exclusions or comparisons to siblings are provided.

    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 'fetched fresh' implying network/caching behavior, and clarifies channel versions, but it does not explain the force parameter, potential side effects, rate limits, or what happens when both section and query are provided. Significant behavioral gaps remain.

    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 concise, front-loaded with the purpose, and each sentence earns its place. It is well-structured, moving from general purpose to specific usage details. No fluff or redundancy, though it could be slightly more detailed without losing conciseness.

    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 4 optional params and an output schema, the description covers the main modes but leaves gaps: it does not address the interaction between section and query (mutually exclusive or combinable), the effect of force, or the output format (though schema exists). It is adequate for basic use but not 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?

    Schema description coverage is 0%, so the description must compensate. It explains section, query, and channel, giving concrete meaning (e.g., 'stable (latest release) or master'), but it does not describe the force parameter at all. The coverage is partial—3 out of 4 params—so it adds value but is incomplete.

    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 fetches the official Zig Language Reference and specifies two modes (section retrieval and query search). It uses a specific verb and resource, but does not explicitly distinguish it from sibling tools like zig_search or zig_std, though the purpose is evident.

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

    Usage Guidelines3/5

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

    The description provides context for usage—it's the language reference fetcher—and explains the two modes, but it does not explicitly state when to use this tool versus alternatives or when not to use it. No exclusions or alternative guidance is given, so usage is implied rather than explicit.

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

  • Behavior3/5

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

    With no annotations, the description carries full burden. It discloses that results are grouped per source with short snippets and that follow-up tools provide full text. However, it does not mention default behaviors (e.g., scope and channel defaults), rate limits, or any additional side effects. Basic behavior is covered but not comprehensively.

    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?

    Two sentences with the purpose front-loaded. The second sentence provides essential hints about scope and follow-up, with no redundancy. It is concise but could be slightly more structured; still, it is efficient and easily scannable.

    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?

    The tool is moderately complex with four parameters and multiple sources. The description covers the search scope and output format (snippets, grouping) but does not explain the channel parameter or how limit affects results. It also leaves ambiguity about whether changelog is searched, given the sibling tools. The output schema likely covers return format, but the description has notable 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?

    Schema description coverage is 0%, so the description must compensate. It explains the scope parameter by listing valid values and clarifies the grouping of results by source. However, it does not explain the 'limit' or 'channel' parameters at all, leaving them to schema defaults. This partial compensation is helpful but incomplete.

    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 it is a unified search across langref, guidance, and std doc comments, with a specific verb and resource. It also distinguishes itself from follow-up tools by indicating it returns snippets rather than full text. However, it does not explicitly contrast with all siblings (e.g., whether changelog is included), so it slightly misses full differentiation.

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

    Usage Guidelines3/5

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

    It implies usage by saying 'follow up with zig_langref/zig_std/perf_guidance for full text', which suggests using this for initial search and those for detailed content. Yet it does not specify when to use this tool instead of directly accessing those tools, nor does it mention any exclusions or scenarios where a search is not appropriate.

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

  • Behavior3/5

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

    No annotations are provided, so the description carries full responsibility for behavioral disclosure. It describes the return values and the underlying comparison action, and implicitly implies a read-only operation (no mutation language). However, it does not explicitly state side effects, network requirements, or error behavior, which for a status tool could be expected. It adds value beyond the name but leaves some gaps.

    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-loading the core purpose and then detailing the output and usage context. Every sentence earns its place with no redundant words, and the structure is easy to parse.

    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?

    The tool is simple (one optional boolean parameter) and has an output schema, so the description needn't explain return structure. However, the lack of any explanation for the 'force' parameter and no mention of prerequisites (e.g., network access or presence of ZIG) leaves gaps. The description covers the main use case but not all context needed for safe and correct invocation.

    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 describes a single boolean parameter 'force' with a default but no description, and schema coverage is 0%. The description does not mention this parameter at all, leaving the agent to guess what 'force' does (e.g., bypass cache, force network fetch). Since there is zero coverage and no explanation, the description fails to provide needed semantics for this parameter.

    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 uses the specific verb 'Compare' with a clear resource ('local `zig version` with the latest upstream release') and enumerates exactly what is returned. It also differentiates from siblings like zig_update by focusing on status rather than modification, so an agent can select it without ambiguity.

    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 when to use the tool: 'before version-sensitive answers' and 'whenever Zig code misbehaves in ways a newer compiler fixes.' It does not mention when not to use it or point to alternatives, which would make it a 5, but the guidance is clear and actionable.

    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 provided, the description carries the burden. It honestly discloses how it works: walking real re-exports and returning doc comments plus declaration text from the exact release. This gives the agent a clear model of behavior and scope. It does not mention side effects, but as a lookup tool, that is expected. No contradictions with annotations (none exist).

    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 concise and well-structured: the first sentence states purpose, the second explains the two modes, and the third gives a preference hint. Every sentence earns its place, and there is no verbose repetition or fluff.

    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?

    For a documentation lookup tool, the description covers the core behavior and most parameters. The output schema exists, so return values need not be described. The main missing piece is the 'force' parameter's effect, which is a notable hole given the tool's simplicity. Overall, it is reasonably complete but not fully exhaustive.

    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 0%, so the description must explain parameters. It explains symbol and query with concrete examples, and channel is implied in the first sentence. However, the 'force' parameter is completely unexplained. With four parameters, leaving one entirely undefined is a notable gap, though the primary modes are well covered.

    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 it provides standard-library docs from a specific channel's released source. It distinguishes itself from siblings like zig_langref and zig_changelog by specifying the resource (standard library) and the operation (returns /// docs and declaration text). The two modes (symbol lookup and query search) are explicitly described.

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

    Usage Guidelines3/5

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

    It provides guidance on when to use symbol vs query ('Prefer exact symbols; use query to discover names'), which helps within the tool. However, it does not explicitly mention alternatives or when not to use this tool (e.g., versus zig_search or zig_langref). The guidance is implied by the tool's focus on std docs, but it lacks explicit exclusion or alternative routing.

    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 to rely on, the description takes full responsibility for disclosing behavior. It states that dry_run changes nothing, that confirm=True combined with dry_run=False applies the upgrade, and warns about the danger of confirm=True without user consent. This is unusually clear for a mutation tool; it also implies a side effect (modifying the local toolchain) transparently.

    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 compact and well-structured: one sentence states the purpose, the next two explain the two modes with their preconditions, and a final imperative warns about misuse. No filler or redundant information; each sentence 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?

    While the description covers the two critical operational aspects (dry-run and confirm), it omits the channel parameter entirely and does not mention what the output schema contains (e.g., what a successful upgrade returns). For a tool that mutates the local environment, the missing channel documentation is a real gap. The safety warning is strong, but the parameter coverage is incomplete, leaving the agent to guess about channel.

    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 description competently explains dry_run and confirm, their defaults, and their interaction. However, the channel parameter is completely ignored. The schema provides no descriptions (0% coverage) and no enums, so the agent has no idea what values channel accepts or how it affects the upgrade (e.g., does 'stable' vs 'master' change the install method or version?). This is a significant gap for a parameter that likely affects the outcome.

    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 a specific action ('upgrade the LOCAL zig toolchain') and distinguishes it from siblings like zig_version_status and zig_changelog which are about checking status or docs. It even explains the two modes (dry_run and apply) and which one is safe by default, leaving no ambiguity about what the tool accomplishes.

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

    Usage Guidelines5/5

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

    Provides explicit when-to-use and when-not-to-use guidance: dry_run is the default, confirm should never be passed without the user explicitly requesting the update. This tells the agent exactly when to apply vs. just preview, and the warning about confirm covers safety. The mention of 'brew upgrade or official tarball' gives practical method context.

    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. It discloses a limitation: snippets are Zig 0.16-era and advises verifying with zig_std. It also notes principles are universal, implying portability. These are behavioral traits beyond a simple 'getter'. It does not explicitly state it is read-only, but the 'curated guidance' framing implies a non-mutating 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 three short sentences, front-loading purpose and then usage. No redundant content; every sentence adds value. It packs routing and caveats efficiently.

    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 simplicity and existing output schema (which covers return format), the description covers usage modes and limitations. It does not specify whether query and topic can be combined, but that is a minor gap. Overall, sufficient for correct invocation.

    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?

    Schema has 0% coverage, so the description must explain parameters. It does: topic=None lists topics, topic='allocation-strategy' returns the guide, query searches across guides. This gives actionable meaning to both params, though it doesn't enumerate all topic values—acceptable because it instructs how to discover them.

    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 states it provides 'Curated guidance for high-performance lightweight software (Zig-first)', a specific resource type. It distinguishes from siblings like zig_std (API reference) and zig_search (search) by focusing on performance guidance. The usage examples (topic listing, specific topic retrieval, query search) further clarify its role.

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

    Usage Guidelines5/5

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

    Explicitly explains how to use without params (topic=None lists topics), with a specific topic (topic='allocation-strategy' returns the guide), and with query (searches across all guides). It also points to zig_std for API verification, indicating when not to rely on this tool for exact APIs. This is clear routing to an alternative.

    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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  • Evaluate tool definition quality.

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