Skip to main content
Glama
DeckProbe MCP Server

DeckProbe MCP Server

Official
by deckflow

DeckProbe MCP Server

Let an agent ask what's inside a PDF, Office, or iWork file — without opening it.

CI npm License: MIT

Install · Tools · Configuration · Security · How it works · DeckProbe

An MCP server that exposes DeckProbe — ffprobe for documents — as four typed tools. Ask for page counts, slide counts, metadata, encryption and macro signals, structure, or integrity, and get back bounded, deterministic JSON with confidence, evidence, and measured I/O cost.

Nothing is rendered, no macro runs, no external reference is followed, and no network connection is opened. It is safe to point at untrusted files.

// 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"
}

Install

Nothing to install ahead of time — npx fetches the server and the engine together.

Claude Code

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

Claude Desktop, Cursor, VS Code, Zed, and anything else reading mcpServers

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

For a pinned install, npm install -g @deckflow/deckprobe-mcp and use deckprobe-mcp as the command.

Requires Node.js 20 or newer. The engine binary arrives as a per-platform optional dependency for macOS, Linux (glibc and musl), and Windows on x86-64 and ARM64; anywhere else the server falls back to the same engine compiled to WebAssembly, so npx works wherever Node does.

Related MCP server: tamperlens-mcp

Tools

Tool

Use it for

probe

Everything about one document

probe_batch

Inventory or triage many documents in one call

list_formats

Which formats are supported, and where support stops

list_targets

The exact target names a format offers

There is also one resource, deckprobe://schema, carrying the report JSON Schema bundled with the running engine.

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 accepts short names (slide_count), canonical names (powerpoint.slide_count), and presets:

Preset

Expands to

@header

Container identity only — format, size, extension match, encryption flag

@summary

Identity, common metadata, and primary structure

@security

Encryption, macros, signatures, external references, active content

@structure

Format-owned counts, names, and dimensions

@assets

Images, media, previews, fonts, embedded objects

@quality

Integrity, repair, extension match, conformance

@format

Every format-specific target at the active level

@all

Everything available at the active level

@summary deliberately omits statistics that need a full-file read. A PDF's page_count is the notable case — ask for it explicitly.

probe_batch

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

One engine process handles the whole batch. Results come back in input order, each with its own report or its own error, so one bad file never spoils the run. Defaults to the compact values view. Literal paths only — expand globs yourself.

list_formats and list_targets

list_targets takes a format (pdf, docx, xlsx, pptx, doc, xls, ppt, key, numbers, pages) and returns each target's aliases, description, value type, minimum level, cost class, and selector membership. Pass detail: "full" for the engine's complete report, including per-target JSON Schema fragments and expanded selector lists.

Both are cached for the lifetime of the server process.

Reading a report

The tool result is the engine's own schema-v2 envelope, unmodified. Two things are worth knowing before consuming it:

  • status: "partial" is not a failure. It means at least one requested target could not be resolved at the requested confidence. It is named in execution.unresolved_targets, and every other result still stands.

  • confidence_score is a fixed constant per label (0.4, 0.7, 0.95, 1.0), not a calibrated probability. 0.95 does not mean the value is right 95% of the time.

Only results with status resolved or estimated carry a value. unknown is common and usually means the document simply does not record that fact.

A failing call returns isError with the engine's error envelope plus one line saying what to do about it. Failures the server itself raises before the engine runs — a missing path, a directory, a path outside the allow-list, an exceeded deadline — use the same envelope shape with an MCP_-prefixed code and origin: "mcp-server".

Configuration

Every setting is an environment variable, set in your client's MCP config. All are optional.

Variable

Default

Meaning

DECKPROBE_MCP_BIN

–

Engine binary to use instead of the bundled one

DECKPROBE_MCP_ROOTS

unrestricted

Allowed directories, separated like PATH

DECKPROBE_MCP_TIMEOUT_MS

30000

Hard per-call deadline on an engine process

DECKPROBE_MCP_MAX_CONCURRENCY

4

Concurrent engine processes

DECKPROBE_MCP_MAX_BATCH

64

Paths accepted by one probe_batch call

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

Security

DeckProbe is built for untrusted input: bounded parsing, no renderer, no macro interpreter, no external-reference resolution, and no network access. This server adds two things on top.

  • Process isolation and a hard deadline. Each probe runs in its own short-lived process, killed if it outruns DECKPROBE_MCP_TIMEOUT_MS.

  • An optional read allow-list. DECKPROBE_MCP_ROOTS pins the reachable tree; paths are symlink-resolved before the check, so a link cannot step around it. The default is unrestricted, matching the CLI the user could run themselves — set it for shared or automated deployments.

Reports describe a document (metadata, counts, signals) rather than reproducing its contents. Note that report values such as a document title are still attacker-controlled strings: the server passes them through as JSON data and never interpolates them into instructions, and a consumer should treat them the same way.

Report a vulnerability privately as described in SECURITY.md.

How it works

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

The server spawns the native DeckProbe CLI rather than calling the WebAssembly build. The CLI reads only the byte ranges a probe plan needs, where the WebAssembly path holds the whole file in memory, and a separate OS process both isolates untrusted parsing and can be killed outright. The engine is chosen in this order:

  1. DECKPROBE_MCP_BIN

  2. the binary that ships with this package's @deckflow/deckprobe dependency

  3. deckprobe on PATH

  4. the bundled WebAssembly engine

The resolved engine is logged to stderr at startup. stdout belongs to the MCP transport and carries nothing else.

MCP server or agent skill?

DeckProbe also ships an Agent Skill that teaches a shell-capable agent to use the CLI directly. Both teach the same vocabulary. Use the skill when the agent has a shell and you want the CLI's full surface; use this server when it does not, or when you want typed arguments validated before the engine ever runs.

Development

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

Contributions are welcome — see CONTRIBUTING.md. The design rationale, including the alternatives that were rejected, is in docs/rfc.md.

License

MIT. See 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.

Inputs: no named parameters.

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.

Inputs: format (required), detail.

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.

Inputs: path (required), view, level, budget, +3 more. Returns: A DeckProbe schema-v2 envelope. See the deckprobe://schema resource.

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.

Inputs: paths (required), view, level, budget, +2 more. Returns: reports

Tool Schema Changelog

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

Loading tool schema changelog…

    TDQS

    A4.7/5.0

    Scored across 4 tools

    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

    ActivityInactive
    ResponsivenessNo recent community issues

    Related MCP Connectors

    Related MCP Servers

    • A
      license
      Not graded
      quality
      Not graded
      maintenance
      Provides AI agents with comprehensive document parsing capabilities including PDF text extraction, OCR, HTML-to-markdown conversion, table extraction, and summarization, optimized for agent workflows.
      72 npm
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Inspects documents for tampering, ineffective redactions, and text aimed at language models before they enter an agent's context, and compares documents to confirm whether they are unchanged.
      4
      72 npm
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to inspect and convert PDF, PowerPoint, Excel, and many other file formats into clean, structured Markdown, with chunking support for long documents.
      Apache 2.0
    • A
      license
      A
      quality
      B
      maintenance
      Enables AI agents to inspect and work with PDF files entirely on the local machine, covering page counts, metadata, layout, encryption permissions, scan-vs-text detection, and page rendering. Generated results land in a temporary workspace as short artifact ids that can be chained between tools and exported to real folders on request.
      12
      49 PyPI
      1
      Apache 2.0