Skip to main content
Glama
gbrlpzz

zig-docs-mcp

by gbrlpzz

zig-docs-mcp

Lokaler Open-Source-MCP-Server + Agent-Fähigkeiten, die immer aktuelle offizielle Zig-Dokumentation für die neueste Version, ein kuratiertes Hochleistungs-Leichtgewicht-Software-Leitfaden-Korpus und ein sicheres, Dry-Run-zuerst-Auto-Update für eine veraltete lokale Zig-Toolchain bereitstellen.

zig-docs-mcp
├── zigdocs                 MCP server (stdio, local, no accounts)
├── guidance/               curated performance guidance (12 topics)
├── skills/zig-docs         agent skill: operating rules for Zig work
└── skills/zig-docs-mcp     agent skill: Python integration (`zdoc` singleton)

Zig verändert sich schnell, und Antworten aus dem Trainingsspeicher werden zwischen Minor-Releases veraltet – 0.16 ersetzte die gesamte I/O-Schicht und verschob Dir von std.fs zu std.Io. Dieser Server ruft offizielle Dokumente und veröffentlichte Std-Quellen pro Aufruf ab (mit Kurz-TTL-Revalidierung), sodass jede Antwort die Version zitiert, aus der sie stammt. Wenn Ihr lokaler Compiler hinter den Dokumenten zurückbleibt, sagt der Server das und bietet ein abgesichertes Upgrade an. Er verändert Ihr System nie ohne ausdrückliche Bestätigung.


Inhaltsverzeichnis

  1. Warum

  2. Wie es aktuell bleibt

  3. Anforderungen

  4. Server installieren

  5. MCP-Client verbinden

  6. Prime-Agent-Integration

  7. MCP-Tool-Referenz

  8. Toolchain-Auto-Update

  9. Leitfaden-Korpus

  10. Konfiguration

  11. Entwicklung

  12. Fehlerbehebung

  13. Lizenz


Related MCP server: Zignet

Warum

  • Dokumente verrotten schnell. Die Layout der Zig-Stdlib verschiebt sich zwischen Minor Releases. Die echten Quellen der aktuellen Version auszuliefern ist die einzige ehrliche Quelle der API-Wahrheit. zig_std löst Symbole auf, indem es tatsächliche Re-Exports im veröffentlichten Baum durchläuft – keine gescrapte Momentaufnahme.

  • Performance-Ratschläge sollten mechanisch sein. Das gebündelte Korpus erklärt Allokationsstrategie, Datenlayout, Comptime, Binary-Größe, Startlatenz, SIMD, Nebenläufigkeit und Benchmarking – fundiert darin, wie Hardware und Laufzeit tatsächlich funktionieren (Cache-Lines, Syscalls, Page Faults), nicht nach Bauchgefühl.

  • Ein zurückgebliebener Compiler macht still alles ungültig. zig_version_status vergleicht Ihre Toolchain bei jedem Check mit dem Upstream-Index, und zig_update bietet einen konkreten, überprüfbaren Upgrade-Plan.

  • Alles ist lokal-zuerst. Der Server läuft auf Ihrem Rechner über stdio. Keine Konten, keine Tokens, keine Telemetrie. Netzwerk geht nur zu ziglang.org für Dokumente, Release-Notizen und Quell-Tarballs.

Wie es aktuell bleibt

  • Zwischengespeicherte Antworten revalidieren gegen ziglang.org, wenn sie älter als 6 Stunden sind (force=true revalidiert sofort). Revalidierung verwendet bedingte GETs (ETag / Last-Modified), ist also günstig.

  • Offline-sicher: Wenn das Netzwerk ausfällt, werden zwischengespeicherte Inhalte mit einem stale-Flag ausgeliefert, statt zu scheitern. (Der erste Lauf braucht einmal Netzwerk.)

  • Std-Quellen stammen aus dem offiziellen src-Tarball pro Release – dem kanonischen Inhalt, selbst wenn GitHub-Release-Tags nachhinken (0.16.0 war auf GitHub nicht getaggt, als dies gebaut wurde). Der Tarball wird einmal pro Version heruntergeladen und nur lib/std/** wird extrahiert.

  • Der Parameter channel wählt stable (aktuelles Release, Standard) oder master (nächtlich), sodass Sie Änderungen des nächsten Releases Vorschau ansehen können.

Cache-Layout (~/.cache/zig-docs-mcp/, überschreibbar mit ZIG_DOCS_MCP_CACHE):

~/.cache/zig-docs-mcp/
├── http/                    upstream bodies + ETag/Last-Modified metadata
├── langref-0.16.0.json      parsed reference sections (per version)
├── notes-0.16.0.json        release-notes digest
├── zig-0.16.0-src.tar.xz    source tarball cache
└── src/0.16.0/lib/std/      extracted std sources (550 files)

Voraussetzungen

  • Python ≥ 3.10 und uv

  • macOS oder Linux (Auto-Update unterstützt Homebrew und eigenständige Installationen; Windows bekommt einen funktionierenden Plan-Ausdruck, aber noch keine Tarball-Strategie)

  • Netzwerkzugriff auf ziglang.org für erste Abrufe und Revalidierung

Server installieren

git clone https://github.com/gbrlpzz/zig-docs-mcp
cd zig-docs-mcp
uv tool install .          # installs the `zigdocs` command on your PATH
zigdocs --help             # verify

Lieber nicht installieren? Führen Sie ihn direkt aus dem Klon aus:

uv run --project ~/zig-docs-mcp zigdocs

MCP-Client verbinden

Jeder MCP-Client, der stdio spricht. Zeigen Sie ihn auf den zigdocs-Befehl:

{
  "mcpServers": {
    "zig-docs": {
      "command": "zigdocs"
    }
  }
}

Ohne globale Installation verwenden Sie den Klon direkt:

{
  "mcpServers": {
    "zig-docs": {
      "command": "uv",
      "args": ["run", "--project", "/path/to/zig-docs-mcp", "zigdocs"]
    }
  }
}

Prime-Agent-Integration

Zwei Fähigkeiten sind in diesem Repository enthalten. Verlinken Sie sie und starten Sie die Sitzung neu (oder führen Sie /reload aus):

ln -sfn ~/zig-docs-mcp/skills/zig-docs     ~/.agents/skills/zig-docs
ln -sfn ~/zig-docs-mcp/skills/zig-docs-mcp ~/.agents/skills/zig-docs-mcp

Dann, aus dem Agent-Kernel:

from zig_docs_mcp import zdoc

await zdoc.zig_version_status()                       # local vs latest upstream
await zdoc.zig_update()                               # dry-run upgrade plan
await zdoc.zig_update(dry_run=False, confirm=True)    # apply after user agrees
await zdoc.zig_langref(section="Errors")              # fresh language reference
await zdoc.zig_std(symbol="std.heap.ArenaAllocator")  # std docs from released source
await zdoc.zig_changelog()                            # what changed in the release
await zdoc.perf_guidance(topic="allocation-strategy") # curated guidance
await zdoc.zig_search(query="vectorization")          # search everything at once

Aufrufe geben ihr Ergebnis als JSON-String zurück (Vollthemen-Leitfaden-Lesevorgänge geben rohes Markdown zurück); parsen Sie mit json.loads(...), wenn Sie Felder wie version oder docs benötigen. Argumente sind nur-Schlüsselwort. Der Serverbefehl wird in dieser Reihenfolge aufgelöst: ZIG_DOCS_MCP_CMD, ein zigdocs auf dem PATH, dann uv run --project gegen ZIG_DOCS_MCP_REPO (Standard ~/zig-docs-mcp).

skills/zig-docs/SKILL.md enthält die Betriebsregeln, denen der Agent folgt: zuerst Version prüfen, Dokumente vor Code, die Dokumentversion zitieren und niemals ein Update ohne ausdrückliche Zustimmung des Benutzers anwenden.

MCP-Tool-Referenz

zig_version_status

Vergleicht das lokale zig version mit dem neuesten Upstream-Release.

{
 "local_version": "0.16.0",
 "local_path": "/opt/homebrew/bin/zig",
 "latest_stable": "0.16.0",
 "master": "0.17.0-dev.1818+7051f8e73",
 "up_to_date": true
}

Wenn die lokale Toolchain älter ist, fügt die Antwort behind und einen suggestion hinzu, der auf zig_update verweist (illustratives Beispiel):

{
 "local_version": "0.15.2",
 "latest_stable": "0.16.0",
 "up_to_date": false,
 "behind": "local 0.15.2 < latest 0.16.0",
 "suggestion": "Call the zig_update tool (dry-run first) to upgrade the local toolchain to the latest stable release."
}

zig_update

Aktualisiert die lokale Toolchain. Dry-Run ist die Standardeinstellung – er gibt den genauen Plan aus und ändert nichts. Anwenden erfordert dry_run=false, confirm=true. Siehe Toolchain-Auto-Update.

zig_langref

Offizielle Sprachreferenz, frisch für die Kanalversion abgerufen.

  • section="Errors" → vollständiger Abschnittstext (Codeblöcke erhalten):

### Error Set Type
An error set is like an enum. However, each error name across the entire
compilation gets assigned an unsigned integer greater than 0. ...
  • query="vector" → nach Rangfolge sortierte Abschnittstreffer:

[{"section_id": "Vectors", "title": "Vectors§"},
 {"section_id": "Builtin-Functions", "title": "Builtin Functions§"}]
  • keine Argumente → die Liste aller Abschnitts-IDs.

zig_std

Stdlib-Dokumentation aus der exakten veröffentlichten Quelle. Symbolauflösung läuft durch echte Re-Exports (std.zig → heap.zig → heap/ArenaAllocator.zig), folgt @import-Aliasen und gibt die ///-Dokumente plus den Deklarationstext aus dieser Version zurück:

{
 "symbol": "std.ArrayList",
 "version_source": "0.16.0",
 "file": "lib/std/std.zig",
 "line": 49,
 "declaration": "pub fn ArrayList(comptime T: type) type {\n    return array_list.Aligned(T, null);\n}",
 "docs": "A contiguous, growable list of items in memory. This is a wrapper around a\nslice of `T` values. ..."
}

Wenn ein Name keine einfache Top-Level-Deklaration im durchlaufenen Namespace ist (Layouts verschieben sich zwischen Releases), fällt das Tool auf eine korpusweite Suche nach Top-Level-Deklarationen zurück, beste Übereinstimmung zuerst – z. B. std.fs.Dir auf 0.16 zeigt korrekt lib/std/Io/Dir.zig. query="arena" durchsucht Std-Doc-Kommentare direkt.

zig_changelog

Release-Notizen-Digest für die aktuelle Kanalversion: Abschnittstitel plus eine kurze Zusammenfassung jeweils. Nützlich direkt nach einem Release (zig_changelog(force=true)).

perf_guidance

Kuratierte Hinweise für Hochleistungs-Leichtgewicht-Software. Keine Argumente listet Themen auf; topic="allocation-strategy" gibt den vollständigen Leitfaden zurück (rohes Markdown mit Prinzip / Mechanik / Zig-Idiom / Anti-Muster / Faustregeln); query=... durchsucht alle Leitfäden.

Einheitliche Suche über Langref, Std-Doc-Kommentare und Leitfäden:

{"query": "vectorization", "langref": [...], "guidance": [...], "std": [...], "std_version": "0.16.0"}

scope grenzt ein: all (Standard) | langref | std | guidance.

Toolchain-Auto-Update

zig_update wählt automatisch eine Strategie:

  1. Homebrew-verwaltetes Zig (Binary löst innerhalb des Brew-Präfixes auf) → brew upgrade zig:

{
 "mode": "dry-run (nothing changed). Re-run with confirm=true to apply.",
 "target_version": "0.16.0",
 "current": "0.16.0",
 "strategy": "homebrew",
 "command": ["brew", "upgrade", "zig"],
 "note": "Homebrew formula may lag the newest release slightly."
}
  1. Eigenständige Installation (offizieller Tarball, jeder andere Ort) → lädt den Plattform-Tarball aus dem Upstream-Index herunter, extrahiert nach ~/.local/opt/zig-<version> und legt einen Shim ~/.local/bin/zig an:

{
 "strategy": "standalone-tarball",
 "download": "https://ziglang.org/download/0.16.0/zig-aarch64-macos-0.16.0.tar.xz",
 "install_dir": "~/.local/opt/zig-0.16.0",
 "steps": ["download ...", "extract ...", "symlink ~/.local/bin/zig -> .../zig/zig"],
 "activation": "~/.local/bin is first on PATH; new zig takes effect immediately"
}

Wenn ~/.local/bin nicht zuerst auf dem PATH steht, sagt der Plan das ausdrücklich – der alte Compiler würde sonst gewinnen, und das Tool sagt Ihnen, wie Sie die Reihenfolge korrigieren.

Sicherheitsregeln:

  • Standard ist ein Dry-Run. Nichts wird heruntergeladen, verschoben oder verlinkt.

  • Anwenden erfordert dry_run=false, confirm=true zusammen.

  • Agenten, die diesen Server verwenden, werden angewiesen, den Plan zu zeigen und die ausdrückliche Zustimmung des Benutzers einzuholen, bevor sie bestätigen.

Leitfaden-Korpus

Zwölf Themen in guidance/, im Rad ausgeliefert und von perf_guidance bedient. Prinzipien sind universell; Snippets sind Zig-0.16-Ära; exakte API-Wahrheit kommt immer von zig_std, nie aus dem Korpus.

Thema

Einzeilige Zusammenfassung

allocation-strategy

Allokator an Lebensdauer anpassen; Arena-Bump-Pointer-Kosten vs. allgemeine Allokator-Buchhaltung; versteckte Allokationen.

data-oriented-design

SoA vs. AoS-Byte-Mathematik auf 64-Byte-Cache-Lines; Hot/Cold-Splitting; MultiArrayList.

comptime-over-runtime

Comptime-Ergebnisse werden rodata/Immediates; Laufzeittabellen kosten schmutzige Seiten.

zero-copy-parsing

Slices sind 16 Bytes; Allokieren pro Token kostet eine Allokation, ein memcpy und Cache-Lines pro Token.

binary-size

Größe = Erreichbarkeit; Strip, Panik-Modi, Abhängigkeitshygiene; kleinerer Text = weniger Start-Page-Faults.

startup-latency

Kein init_array, faule Text-Page-Faults, faule Initialisierung, keine Arbeit vor argv.

memory-layout

Padding-Mathematik, Feldreihenfolge, gepackte Strukturen, @sizeOf-Comptime-Asserts.

simd-and-vectorization

Auto-Vektorisierungsblocker, lane-weise Akkumulation + einzelne Reduktion, @select vs. Verzweigungen.

concurrency-and-io

MESI-Kosten geteilter Schreibvorgänge, Futex-Parken, Syscall-Batching, False-Sharing-Padding.

error-handling-cost

Fehler sind u16-Werte; try ist eine vorhergesagte Verzweigung; kein Unwinding.

benchmarking-methodology

Release-Builds, Aufwärmen, Min/Median über Mittelwert, Senke, um DCE zu schlagen, Zähler.

dependency-lightweightness

Std-zuerst; Abhängigkeiten fügen verlinkten Code und Build-Fragilität hinzu; kleine Dienstprogramme einkaufen.

Konfiguration

Variable

Bedeutung

Standard

ZIG_DOCS_MCP_CACHE

Cache-Verzeichnis

~/.cache/zig-docs-mcp

ZIG_DOCS_MCP_CMD

vollständige Server-Befehlszeile (Skill-Override)

—

ZIG_DOCS_MCP_REPO

Repo-Verzeichnis für den uv run-Fallback

~/zig-docs-mcp

Entwicklung

make sync    # deps
make test    # unit tests (offline; std-source tests skip without warm cache)
make e2e     # spawns the real server over stdio, calls every tool
make fmt     # ruff format + check

Die E2E-Suite braucht beim ersten Lauf Netzwerk (sie wärmt den Cache auf). Unit-Tests, die Symbolauflösung üben, laufen gegen den warmen Std-Quellen-Cache und werden sauber übersprungen, wenn er fehlt.

Fehlerbehebung

  • zigdocs server not found (Prime-Agent-Fähigkeit): installieren Sie mit uv tool install . aus dem Klon, oder setzen Sie ZIG_DOCS_MCP_REPO auf den Klonpfad, oder setzen Sie ZIG_DOCS_MCP_CMD auf eine vollständige Befehlszeile.

  • Erster Lauf schlägt offline fehl: Der Cache startet leer; holen Sie einmal online ab. Danach hält der Stale-Cache-Fallback jedes Tool am Laufen.

  • Ergebnisse wirken nach einem neuen Release veraltet: übergeben Sie force=true (sonst gilt die 6-Stunden-TTL).

  • zig version ist nach einem Update immer noch alt: eine neue Shell ist nötig, und ~/.local/bin muss vor dem vorherigen Installationsverzeichnis auf dem PATH stehen. Der Dry-Run-Plan nennt die genaue Situation für Ihren Rechner.

  • Homebrew-Zig hinkt dem neuesten Release hinterher: Brew-Formeln hinken Releases hinterher; verwenden Sie die eigenständige Strategie (Brew-Formel entfernen, eigenständig installieren), wenn Sie Tag-eins-Versionen brauchen.

Lizenz

MIT – siehe LICENSE.

Available Tools

7 tools
perf_guidanceA

Curated guidance for high-performance lightweight software (Zig-first).

topic=None lists topics. topic='allocation-strategy' returns the guide. query searches across all guides. Principles are universal; snippets are Zig 0.16-era; verify exact APIs with zig_std.

ParametersJSON Schema
NameRequiredDescriptionDefault
queryNo
topicNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A4.6/5.0
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.

zig_changelogC

Release-notes digest for the current channel version: what changed.

ParametersJSON Schema
NameRequiredDescriptionDefault
forceNo
channelNostable

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

C2.8/5.0
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.

zig_langrefB

Official Zig Language Reference, fetched fresh for the channel version.

section= returns that full section. query= searches sections. Neither lists all section ids. channel: 'stable' (latest release) or 'master'.

ParametersJSON Schema
NameRequiredDescriptionDefault
forceNo
queryNo
channelNostable
sectionNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

B3.2/5.0
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.

zig_stdA

Standard-library docs from the EXACT released source of the channel.

symbol='std.fs.Dir.openFile' walks real re-exports and returns the /// docs plus the declaration text from that release. query= searches std doc comments. Prefer exact symbols; use query to discover names.

ParametersJSON Schema
NameRequiredDescriptionDefault
forceNo
queryNo
symbolNo
channelNostable

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A4/5.0
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.

zig_updateA

Upgrade the LOCAL zig toolchain to the latest release, safely.

dry_run=True (default): print the exact plan, change nothing. confirm=True AND dry_run=False: apply it (brew upgrade or official tarball). Never pass confirm=True without the user asking for the update.

ParametersJSON Schema
NameRequiredDescriptionDefault
channelNostable
confirmNo
dry_runNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A4.4/5.0
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.

zig_version_statusA

Compare local zig version with the latest upstream release.

Returns local version/path, latest stable, master, up_to_date flag and, when behind, a suggested next step. Call this before version-sensitive answers and whenever Zig code misbehaves in ways a newer compiler fixes.

ParametersJSON Schema
NameRequiredDescriptionDefault
forceNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A3.8/5.0
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.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 7 tool updatesv0.1.0
    • First observedperf_guidance
    • First observedzig_changelog
    • First observedzig_langref
    • First observedzig_search
    • First observedzig_std
    • First observedzig_update
    • First observedzig_version_status

TDQS

A3.7/5.0

Scored across 7 tools

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.

Maintenance

ActivitySlowing
ResponsivenessNo issues

Related MCP Connectors

Related MCP Servers

  • A
    license
    A
    quality
    D
    maintenance
    Provides Zig language tooling and code analysis, enhancing AI capabilities with Zig-specific functions like code optimization, compute unit estimation, code generation, and recommendations for best practices.
    7
    51
    MIT
  • A
    license
    Not graded
    quality
    C
    maintenance
    Enables AI-powered Zig programming assistance through code generation, debugging, and documentation explanation. Uses local LLM models to provide idiomatic Zig code creation and analysis capabilities.
    34 npm
    10
    Do What The F*ck You Want To Public
  • F
    license
    Not graded
    quality
    C
    maintenance
    MCP server for Zig that connects AI coding assistants to ZLS (Zig Language Server) via LSP. Provides 16 tools for code intelligence (hover, go-to-definition, references, completions, diagnostics, rename, format) and build/test operations.
    7
    -
  • A
    license
    A
    quality
    C
    maintenance
    A high-performance MCP server providing up-to-date documentation for Go, npm, Python, Rust, Docker, Kubernetes, Terraform, and more — fetched from official sources, not training data.
    18
    3
    MIT