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DeckProbe MCP Server

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DeckProbe MCP Server

Lassen Sie einen Agenten fragen, was in einer PDF-, Office- oder iWork-Datei steckt — ohne sie zu öffnen.

CI npm License: MIT

Installation · Tools · Konfiguration · Sicherheit · So funktioniert's · DeckProbe

Ein MCP-Server, der DeckProbeffprobe für Dokumente — als vier typisierte Tools bereitstellt. Fragen Sie nach Seitenzahlen, Folienzahlen, Metadaten, Verschlüsselungs- und Makrosignalen, Struktur oder Integrität, und Sie erhalten begrenztes, deterministisches JSON mit Konfidenz, Belegen und gemessenen I/O-Kosten zurück.

Es wird nichts gerendert, kein Makro ausgeführt, kein externer Verweis verfolgt und keine Netzwerkverbindung geöffnet. Es ist sicher, ihn auf nicht vertrauenswürdige Dateien zu richten.

// probe { "path": "deck.pptx", "targets": ["slide_count"], "view": "values" }
{
  "schema_version": 2,
  "status": "ok",
  "driver": { "id": "powerpoint", "profile": "pptx" },
  "values": { "powerpoint.slide_count": 31 },
  "view": "values"
}

Installation

Vorab ist nichts zu installieren — npx lädt Server und Engine gemeinsam herunter.

Claude Code

claude mcp add deckprobe -- npx -y @deckflow/deckprobe-mcp

Claude Desktop, Cursor, VS Code, Zed und alles andere, das mcpServers liest

{
  "mcpServers": {
    "deckprobe": {
      "command": "npx",
      "args": ["-y", "@deckflow/deckprobe-mcp"]
    }
  }
}

Für eine Installation mit fester Version: npm install -g @deckflow/deckprobe-mcp ausführen und deckprobe-mcp als Befehl verwenden.

Erfordert Node.js 20 oder neuer. Die Engine-Binärdatei wird als optionale Abhängigkeit pro Plattform für macOS, Linux (glibc und musl) und Windows auf x86-64 und ARM64 mitgeliefert; überall sonst fällt der Server auf dieselbe als WebAssembly kompilierte Engine zurück, sodass npx überall dort funktioniert, wo Node läuft.

Related MCP server: flexorch-mcp

Tools

Tool

Verwendungszweck

probe

Alles über ein einzelnes Dokument

probe_batch

Inventarisierung oder Triage vieler Dokumente in einem Aufruf

list_formats

Welche Formate unterstützt werden — und wo die Unterstützung endet

list_targets

Die genauen Zielnamen, die ein Format bietet

Es gibt außerdem eine Ressource, deckprobe://schema, die das mit der laufenden Engine gebündelte JSON-Schema des Berichts trägt.

probe

{
  "path": "reports/q3.pptx",
  "targets": ["@summary", "@security"],  // presets, short names, or canonical names
  "level": "metadata",                   // header | metadata | deep
  "min_confidence": "high",              // low | medium | high | exact
  "target_confidence": { "slide_count": "exact" },
  "view": "report",                      // report | values
  "budget": { "max_physical_bytes": 8388608, "timeout_ms": 1000 }
}

targets akzeptiert Kurznamen (slide_count), kanonische Namen (powerpoint.slide_count) und Presets:

Preset

Erweitert sich zu

@header

Nur die Container-Identität — Format, Größe, Erweiterungsabgleich, Verschlüsselungs-Flag

@summary

Identität, allgemeine Metadaten und primäre Struktur

@security

Verschlüsselung, Makros, Signaturen, externe Verweise, aktive Inhalte

@structure

Formateigene Zählwerte, Namen und Dimensionen

@assets

Bilder, Medien, Vorschauen, Schriften, eingebettete Objekte

@quality

Integrität, Reparatur, Erweiterungsabgleich, Konformität

@format

Jedes formatspezifische Ziel auf der aktiven Ebene

@all

Alles, was auf der aktiven Ebene verfügbar ist

@summary lässt bewusst Statistiken aus, die ein vollständiges Lesen der Datei erfordern. Der page_count einer PDF ist der markante Fall — fragen Sie explizit danach.

probe_batch

{ "paths": ["a.pdf", "b.pptx", "c.xlsx"], "targets": ["@security"] }

Ein einziger Engine-Prozess übernimmt den gesamten Stapel. Ergebnisse kommen in Eingabereihenfolge zurück, jeweils mit eigenem Bericht oder eigenem Fehler, sodass eine fehlerhafte Datei den Lauf nie verdirbt. Standardmäßig wird die kompakte values-Ansicht verwendet. Nur literale Pfade — expandieren Sie Globs selbst.

list_formats und list_targets

list_targets nimmt ein format entgegen (pdf, docx, xlsx, pptx, doc, xls, ppt, key, numbers, pages) und liefert für jedes Ziel dessen Aliase, Beschreibung, Werttyp, Mindestebene, Kostenklasse und Selektorzugehörigkeit. Übergeben Sie detail: "full", um den vollständigen Bericht der Engine zu erhalten, einschließlich JSON-Schema-Fragmenten pro Ziel und erweiterten Selektorlisten.

Beide werden für die Lebensdauer des Serverprozesses zwischengespeichert.

Einen Bericht lesen

Das Tool-Ergebnis ist das eigene Schema-v2-Envelope der Engine, unverändert. Zwei Dinge sollten Sie wissen, bevor Sie es verarbeiten:

  • status: "partial" ist kein Fehler. Es bedeutet, dass mindestens ein angefordertes Ziel nicht mit der angeforderten Konfidenz aufgelöst werden konnte. Es wird in execution.unresolved_targets benannt, und alle anderen Ergebnisse behalten ihre Gültigkeit.

  • confidence_score ist eine feste Konstante pro Label (0.4, 0.7, 0.95, 1.0), keine kalibrierte Wahrscheinlichkeit. 0.95 bedeutet nicht, dass der Wert in 95 % der Fälle richtig ist.

Nur Ergebnisse mit dem Status resolved oder estimated tragen einen value. unknown ist häufig und bedeutet meist, dass das Dokument diese Tatsache schlicht nicht festhält.

Ein fehlgeschlagener Aufruf liefert isError mit dem Fehler-Envelope der Engine plus einer Zeile, die sagt, was zu tun ist. Fehler, die der Server selbst auslöst, bevor die Engine läuft — ein fehlender Pfad, ein Verzeichnis, ein Pfad außerhalb der Zulassungsliste, ein überschrittenes Zeitlimit — verwenden dieselbe Envelope-Form mit einem Code mit MCP_-Präfix und origin: "mcp-server".

Konfiguration

Jede Einstellung ist eine Umgebungsvariable, die in der MCP-Konfiguration Ihres Clients gesetzt wird. Alle sind optional.

Variable

Standard

Bedeutung

DECKPROBE_MCP_BIN

Engine-Binärdatei, die anstelle der gebündelten verwendet wird

DECKPROBE_MCP_ROOTS

uneingeschränkt

Erlaubte Verzeichnisse, getrennt wie PATH

DECKPROBE_MCP_TIMEOUT_MS

30000

Hartes Zeitlimit pro Aufruf für einen Engine-Prozess

DECKPROBE_MCP_MAX_CONCURRENCY

4

Gleichzeitige Engine-Prozesse

DECKPROBE_MCP_MAX_BATCH

64

Pfade, die ein einziger probe_batch-Aufruf akzeptiert

{
  "deckprobe": {
    "command": "npx",
    "args": ["-y", "@deckflow/deckprobe-mcp"],
    "env": { "DECKPROBE_MCP_ROOTS": "/Users/me/Documents:/Users/me/Downloads" }
  }
}

Sicherheit

DeckProbe ist für nicht vertrauenswürdige Eingaben gebaut: begrenztes Parsing, kein Renderer, kein Makro-Interpreter, keine Auflösung externer Verweise und kein Netzwerkzugriff. Dieser Server fügt obendrein zwei Dinge hinzu.

  • Prozessisolation und ein hartes Zeitlimit. Jeder Probevorgang läuft in einem eigenen kurzlebigen Prozess, der abgebrochen wird, wenn er DECKPROBE_MCP_TIMEOUT_MS überschreitet.

  • Eine optionale Lese-Zulassungsliste. DECKPROBE_MCP_ROOTS begrenzt den erreichbaren Verzeichnisbaum; Pfade werden vor der Prüfung symlink-aufgelöst, sodass ein Link die Liste nicht umgehen kann. Der Standard ist uneingeschränkt und entspricht dem CLI, das der Benutzer selbst ausführen könnte — setzen Sie sie für gemeinsame oder automatisierte Bereitstellungen.

Berichte beschreiben ein Dokument (Metadaten, Zählwerte, Signale), statt dessen Inhalte zu reproduzieren. Beachten Sie, dass Berichtswerte wie ein Dokumenttitel dennoch vom Angreifer kontrollierte Zeichenketten sind: Der Server gibt sie als JSON-Daten unverändert weiter und interpoliert sie nie in Anweisungen; ein Konsument sollte sie genauso behandeln.

Melden Sie eine Schwachstelle vertraulich, wie in SECURITY.md beschrieben.

So funktioniert's

MCP client
    │  JSON-RPC over stdio
    ▼
deckprobe-mcp ── validates arguments, resolves the path, maps the result
    │  argv + stdout (one process per probe, or one --jsonl process per batch)
    ▼
DeckProbe engine ── plans the cheapest paths that answer the request

Der Server startet das native DeckProbe-CLI, anstatt die WebAssembly-Version aufzurufen. Das CLI liest nur die Bytebereiche, die ein Probe-Plan benötigt, während der WebAssembly-Pfad die gesamte Datei im Speicher hält; ein separater Betriebssystemprozess isoliert zum einen das Parsen nicht vertrauenswürdiger Daten und kann zum anderen jederzeit beendet werden. Die Engine wird in dieser Reihenfolge ausgewählt:

  1. DECKPROBE_MCP_BIN

  2. die Binärdatei, die mit der @deckflow/deckprobe-Abhängigkeit dieses Pakets geliefert wird

  3. deckprobe im PATH

  4. die gebündelte WebAssembly-Engine

Die aufgelöste Engine wird beim Start auf stderr protokolliert. stdout gehört zum MCP-Transport und enthält nichts anderes.

MCP-Server oder Agent Skill?

DeckProbe wird außerdem mit einer Agent Skill ausgeliefert, die einem shell-fähigen Agenten beibringt, das CLI direkt zu verwenden. Beide vermitteln denselben Wortschatz. Nutzen Sie die Skill, wenn der Agent eine Shell hat und Sie den vollständigen Funktionsumfang des CLI möchten; nutzen Sie diesen Server, wenn das nicht der Fall ist oder wenn Sie möchten, dass typisierte Argumente validiert werden, bevor die Engine überhaupt läuft.

Entwicklung

npm install
npm test          # typecheck, lint, build, and the full suite
npm run test:watch

Beiträge sind willkommen — siehe CONTRIBUTING.md. Die Design-Begründung, einschließlich der verworfenen Alternativen, findet sich in docs/rfc.md.

Lizenz

MIT. Siehe LICENSE.

Available Tools

4 tools
list_formatsList supported formatsA
Read-onlyIdempotent

List the document formats DeckProbe can inspect: drivers, the extensions each one handles, and where support stops. Call this when you are unsure whether a file type is supported at all.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds valuable context about the exact output content (drivers, extensions, support limitations), which goes beyond the annotations. No contradictions with annotations.

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, with the primary purpose and scope front-loaded. It avoids redundancy and every sentence earns its place—the first states what it lists, the second when to call it. No unnecessary detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple, parameterless list tool with no output schema, the description fully explains what the tool returns (drivers, extensions, and support limits). There is nothing missing for an agent to correctly invoke it and interpret the result. Complexity is low, so this is complete.

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?

The tool has zero parameters, so the schema is fully covered (100% by default). There is nothing to add about parameters; the description doesn't need to explain any. The baseline for zero parameters is 4, and no additional info is required.

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 a specific verb ('List'), a clear resource ('document formats DeckProbe can inspect'), and specifies the content (drivers, extensions, and where support stops). It effectively distinguishes itself from sibling tools like probe and list_targets by focusing on format capabilities rather than probing or target listing.

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 gives explicit when-to-use guidance: 'Call this when you are unsure whether a file type is supported at all.' It doesn't mention alternatives, but the trigger condition is clear and implies that if you have a specific file, you would use probe instead. It could be improved by naming the sibling tools explicitly, but the guidance is sufficient.

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

list_targetsList targets for a formatA
Read-onlyIdempotent

List every target a format supports, with its aliases, value type, minimum probe level, cost class, and which @selectors include it. Call this before naming a target you have not already seen — probe rejects an unknown one rather than guessing.

ParametersJSON Schema
NameRequiredDescriptionDefault
detailNocompact (default): target names, aliases, descriptions, levels, and selector membership. full: the complete report, including each target's JSON Schema fragment and every selector's expanded member list.
formatYesA format profile from list_formats, such as "pdf", "docx", "xlsx", "pptx", "doc", "xls", "ppt", "key", "numbers", or "pages".

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint=false, and destructiveHint=false, covering safety. The description adds behavioral context by spelling out returned fields and the probe rejection behavior, which matters for planning calls. No contradictions.

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?

Two sentences front-load the core purpose and output contents, then give one practical usage rule. No filler or repetition of schema details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With a rich annotation set, fully documented parameters, and a description that names the output fields and the prerequisite call, an agent has enough to invoke the tool correctly even with no output schema.

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 coverage is 100%, so the schema already explains format and detail fully, including enumerations and examples. The description adds no new parameter-level semantics beyond naming the report contents, so baseline 3 is appropriate.

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 a specific verb (list) and resource (targets for a given format), enumerates exactly what is included (aliases, value type, minimum probe level, cost class, selector membership), and contrasts with probe by stating probe rejects unknown targets. This distinguishes it from sibling tools list_formats and probe.

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?

It explicitly instructs when to call: before naming a target not already seen, because probe rejects unknowns rather than guessing. It also ties the format parameter to list_formats, implying the prerequisite and differentiating from list_formats.

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

probeProbe a documentA
Read-onlyIdempotent

Read facts about one local PDF, Microsoft Office, or Apple iWork document without opening or rendering it: page, slide, and sheet counts; title, author, and dates; encryption, macro, signature, and active-content signals; structure; embedded assets; and integrity. Handles .pdf, .docx/.xlsx/.pptx, legacy .doc/.xls/.ppt, and modern .key/.numbers/.pages.

Start with targets ["@summary"], or ["@security"] to triage an untrusted file. Prefer this over unzipping the document or parsing its bytes by hand.

Reports facts ABOUT the document, never its text: it does not extract, render, run macros, follow external references, or open a network connection.

ParametersJSON Schema
NameRequiredDescriptionDefault
pathYesPath to the document. The filename extension selects the format driver, and the container is then verified against it.
viewNoreport: full evidence — value, confidence, path, and cost per target. values: a compact target-to-value map.
levelNoProbe budget and eligible paths. header: identity only. metadata (default). deep: higher-cost paths, needed only when a target's min_level says so.
budgetNoOverride the level's resource limits. Raise after a BUDGET_EXCEEDED error.
targetsNoShort names (slide_count), canonical names (powerpoint.slide_count), or presets: @header, @summary, @security, @structure, @assets, @quality, @format, @all. Defaults to the driver's own set. Call list_targets rather than guessing a name. @summary omits statistics needing a full-file read, so ask for a PDF's page_count explicitly.
min_confidenceNoWeakest evidence a path may offer. Default high; lower it to accept an approximation.
target_confidenceNoPer-target override, e.g. {"slide_count": "exact"} to force the authoritative path.

Output Schema

ParametersJSON Schema
NameRequiredDescription
statusNo
schema_versionNo

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is covered. The description adds critical behavioral context beyond those hints: it does not extract, render, run macros, follow external references, or open a network connection; it handles legacy formats; it can hit resource limits (referenced by 'Raise after a BUDGET_EXCEEDED error'). This is exactly the kind of non-obvious behavior an agent needs to trust the tool with untrusted files.

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 well-structured: opening scope sentence, format list, usage hint, and a final 'does not' sentence. It is front-loaded with the core purpose and scoping. It earns its sentences; only a minor redundancy exists (the 'Prefer this over...' sentence partially repeats the 'does not' list). Not a 5, but far above the typical terse definition.

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 tool with 7 parameters, nested budget object, output schema present, and complex behavior (format drivers, confidence levels, presets, resource limits), the description provides substantial orientation: preset suggestions, the @summary caveat, the budget-error hint, and a clear non-extraction guarantee. The description does not explain what each target means, but it correctly defers to list_targets. So it's complete enough without being exhaustive.

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 description coverage is 100%, so the schema already documents all 7 parameters well. The description adds important cross-references that the schema alone does not capture: the distinction between @summary and full-read statistics, the warning that @summary omits page_count so ask explicitly, and that list_targets should be used rather than guessing names. This goes beyond a baseline 3 by explaining how the parameters interact with presets and the driver's default set.

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 opens with a specific verb ('Read facts about one local PDF, Microsoft Office, or Apple iWork document') plus a precise resource list (page/slide/sheet counts, title/author/dates, encryption, macros, structure, assets, integrity). The scope is explicit: it reports facts ABOUT the document, never extracts text, renders, runs macros, or opens connections. It also names sibling tools (list_targets, probe_batch) and distinguishes from unzipping/byte-parsing by hand. This is clear and differentiated.

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?

The description explicitly advises 'Start with targets ["@summary"], or ["@security"] to triage an untrusted file.' and 'Prefer this over unzipping the document or parsing its bytes by hand.' It also warns about @summary omitting statistics and instructs to 'Call list_targets rather than guessing a name.' This provides direct when-to-use and when-not-to-use guidance, plus pointers to alternatives.

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

probe_batchProbe several documentsA
Read-onlyIdempotent

Probe many local documents in one call — inventory a folder, triage a batch of uploads, or compare a set of files. One engine process handles the whole batch, so this is much cheaper than calling probe once per file.

Takes literal paths; expand any glob yourself first. Returns one entry per path, in the order given, each carrying that file's report or its own error envelope. A file that fails does not affect the others.

Defaults to the compact "values" view because inventory rarely needs per-target evidence; pass view: "report" when it does.

ParametersJSON Schema
NameRequiredDescriptionDefault
viewNoreport: full evidence — value, confidence, path, and cost per target. values: a compact target-to-value map.
levelNoProbe budget and eligible paths. header: identity only. metadata (default). deep: higher-cost paths, needed only when a target's min_level says so.
pathsYesDocument paths, at most 64 per call. Literal paths only.
budgetNoOverride the level's resource limits. Raise after a BUDGET_EXCEEDED error.
targetsNoShort names (slide_count), canonical names (powerpoint.slide_count), or presets: @header, @summary, @security, @structure, @assets, @quality, @format, @all. Defaults to the driver's own set. Call list_targets rather than guessing a name. @summary omits statistics needing a full-file read, so ask for a PDF's page_count explicitly.
min_confidenceNoWeakest evidence a path may offer. Default high; lower it to accept an approximation.

Output Schema

ParametersJSON Schema
NameRequiredDescription
reportsYesOne entry per requested path, in order. A per-file failure is confined to it.

TDQS

A4.8/5.0
Behavior5/5

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

The description adds substantial behavioral detail beyond the annotations: one engine process for the batch, per-path results in order, error envelopes per file, failure isolation, default view and when to switch. Annotations already cover read-only/idempotent/destructive, and the description does not contradict them.

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?

Three sentences, zero fluff. The first sentence front-loads purpose and use cases; the second covers path handling and return behavior; the third gives view guidance. Every sentence earns its place.

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 tool with 6 parameters, nested objects, and a full output schema, the description covers the essential usage context: batch behavior, order of results, error isolation, and view default. It does not mention budget override or target selection, but those are adequately documented in the schema. The description is 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 coverage is 100%, so the baseline is 3. The description adds valuable semantic guidance: 'Takes literal paths; expand any glob yourself first' clarifies the paths parameter, and the view default rationale ('inventory rarely needs per-target evidence') adds context beyond the schema. It does not elaborate on every parameter, but the key ones receive useful extra meaning.

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 probes many local documents in one call, listing concrete use cases (inventory a folder, triage a batch, compare files). It distinguishes itself from the sibling 'probe' by explicitly being the batch counterpart.

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?

The description explicitly explains when to use this tool ('Probe many local documents in one call'), gives practical scenarios, and contrasts cost efficiency ('much cheaper than calling probe once per file'). It also gives guidance on view selection ('pass view: report when it does').

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. Dates show when Glama detected each change.

  1. 4 tool updatesv0.1.1
    • First observedlist_formats
    • First observedlist_targets
    • First observedprobe
    • First observedprobe_batch

TDQS

A4.7/5.0
Disambiguation5/5

Each tool has a wholly distinct purpose: probe handles a single file, probe_batch handles multiples, list_formats enumerates supported file types, and list_targets enumerates probe targets. There is no overlap or ambiguity between them.

Naming Consistency5/5

All tools follow a consistent lowercase_snake_case convention with clear verb prefixes: probe, probe_batch, list_formats, list_targets. The naming style is uniform and predictable, making the tool set easy to reason about.

Tool Count5/5

With exactly 4 tools, the server is tightly scoped for its purpose of document inspection. Each tool fills a necessary role (single file, batch, format discovery, target discovery) without redundancy or bloat, fitting well within the ideal 3–15 range.

Completeness5/5

The surface covers all core workflows: probing an individual file, probing many files efficiently, discovering supported formats, and enumerating probe targets for a given format. There are no obvious dead ends or missing operations for the server's stated purpose.

Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

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