DeckProbe MCP Server
OfficialDeckProbe MCP 服务器
让智能体无需打开 PDF、Office 或 iWork 文件,即可探知其中内容。
安装 · 工具 · 配置 · 安全 · 工作原理 · DeckProbe
一个 MCP 服务器,将
DeckProbe —— 文档领域的 ffprobe —— 以
四个类型化工具的形式暴露出来。查询页数、幻灯片数、元数据、加密和
宏信号、结构或完整性,即可获得有界、确定性的 JSON
结果,其中包含置信度、证据和实测 I/O 开销。
不渲染任何内容,不运行宏,不跟随任何外部引用,也不 打开任何网络连接。将其指向不受信任的文件是安全的。
// 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"
}安装
无需预先安装任何内容 —— npx 会同时获取服务器和引擎。
Claude Code
claude mcp add deckprobe -- npx -y @deckflow/deckprobe-mcpClaude Desktop、Cursor、VS Code、Zed 以及任何其他读取 mcpServers 的客户端
{
"mcpServers": {
"deckprobe": {
"command": "npx",
"args": ["-y", "@deckflow/deckprobe-mcp"]
}
}
}如需固定版本安装,请执行 npm install -g @deckflow/deckprobe-mcp,并使用
deckprobe-mcp 作为命令。
需要 Node.js 20 或更高版本。引擎二进制文件以按平台区分的
可选依赖形式提供,支持 macOS、Linux(glibc 和 musl)以及 Windows 的 x86-64 和
ARM64 架构;在其他任何平台上,服务器会回退到同一引擎的
WebAssembly 编译版本,因此只要 Node 可用,npx 就能在任何地方工作。
Related MCP server: flexorch-mcp
工具
工具 | 用途 |
| 获取单个文档的所有信息 |
| 在一次调用中盘点或分类多个文档 |
| 支持哪些格式,以及支持范围到哪里为止 |
| 某格式提供的精确目标名称 |
此外还有一个资源 deckprobe://schema,携带随运行中的引擎一起打包的报告 JSON Schema。
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 接受短名称(slide_count)、规范名称
(powerpoint.slide_count)以及预设:
预设 | 展开为 |
| 仅容器身份 —— 格式、大小、扩展名匹配、加密标志 |
| 身份、常见元数据和主要结构 |
| 加密、宏、签名、外部引用、活动内容 |
| 格式自有的计数、名称和尺寸 |
| 图像、媒体、预览、字体、嵌入对象 |
| 完整性、修复、扩展名匹配、一致性 |
| 当前级别下所有格式特定的目标 |
| 当前级别下所有可用的目标 |
@summary 刻意省略了需要完整读取文件才能得到的统计信息。PDF 的
page_count 就是典型例子 —— 请显式请求它。
probe_batch
{ "paths": ["a.pdf", "b.pptx", "c.xlsx"], "targets": ["@security"] }一个引擎进程处理整个批次。结果按输入顺序返回,
每个结果都带有自己的报告或自己的错误,因此一个坏文件永远不会破坏整个运行。
默认使用紧凑的 values 视图。仅支持字面路径 —— 请自行展开通配符。
list_formats 和 list_targets
list_targets 接受一个 format(pdf、docx、xlsx、pptx、doc、xls、
ppt、key、numbers、pages),并返回每个目标的别名、
描述、值类型、最低级别、开销类别和选择器成员资格。
传入 detail: "full" 可获取引擎的完整报告,包括每个目标的
JSON Schema 片段和展开的选择器列表。
两者都会在服务器进程的整个生命周期内缓存。
阅读报告
工具结果就是引擎自身的 schema-v2 信封,未做任何修改。在消费它之前, 有两件事值得了解:
status: "partial"不是失败。 它意味着至少有一个请求的 目标无法在请求的置信度下被解析。该目标会在execution.unresolved_targets中被点名,而所有其他结果仍然有效。confidence_score是每个标签的固定常量(0.4、0.7、0.95、1.0),不是校准后的概率。0.95并不意味着该值在 95% 的情况下是正确的。
只有状态为 resolved 或 estimated 的结果才带有 value。unknown 很常见,
通常意味着文档根本没有记录该事实。
失败的调用会返回 isError,其中包含引擎的错误信封,外加一行
说明该如何处理。服务器在引擎运行之前自行引发的失败 —— 路径缺失、目录、
允许列表之外的路径、超出截止时间 —— 使用相同的信封形状,带有 MCP_ 前缀的代码和
origin: "mcp-server"。
配置
每个设置都是一个环境变量,在客户端的 MCP 配置中设置。 所有变量都是可选的。
变量 | 默认值 | 含义 |
| – | 要使用的引擎二进制文件,替代随附的二进制文件 |
| 不受限制 | 允许的目录,按 |
|
| 引擎进程的每次调用硬性截止时间 |
|
| 并发引擎进程数 |
|
| 一次 |
{
"deckprobe": {
"command": "npx",
"args": ["-y", "@deckflow/deckprobe-mcp"],
"env": { "DECKPROBE_MCP_ROOTS": "/Users/me/Documents:/Users/me/Downloads" }
}
}安全
DeckProbe 专为不受信任的输入而构建:有界解析、无渲染器、无宏 解释器、无外部引用解析、无网络访问。此 服务器在此基础上增加了两项内容。
进程隔离和硬性截止时间。 每次探测都在自己独立的 短生命周期进程中运行,如果超过
DECKPROBE_MCP_TIMEOUT_MS则被终止。可选的读取允许列表。
DECKPROBE_MCP_ROOTS固定了可访问的 目录树;路径在检查前会先解析符号链接,因此链接无法绕过它。 默认是不受限制的,与用户自己可以运行的 CLI 一致 —— 请在共享或自动化部署中设置它。
报告描述文档(元数据、计数、信号),而不是重现其 内容。请注意,报告值(如文档标题)仍然是攻击者控制的字符串: 服务器将它们作为 JSON 数据传递,绝不会将它们插入到指令中, 消费者应以同样的方式对待它们。
请按照 SECURITY.md 中的描述私下报告漏洞。
工作原理
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服务器启动原生 DeckProbe CLI,而不是调用 WebAssembly 构建。CLI 只读取探测计划所需的字节范围,而 WebAssembly 路径会将整个文件保存在内存中,并且独立的操作系统进程既能 隔离不受信任的解析,也可以被直接终止。引擎按以下顺序选择:
DECKPROBE_MCP_BIN随此包的
@deckflow/deckprobe依赖一起提供的二进制文件PATH上的deckprobe随附的 WebAssembly 引擎
解析到的引擎会在启动时记录到 stderr。stdout 属于 MCP 传输层,不携带任何其他内容。
MCP 服务器还是智能体技能?
DeckProbe 还附带一个 Agent Skill, 用于教会具备 shell 能力的智能体直接使用 CLI。两者教授相同的 词汇表。当智能体拥有 shell 且你想要 CLI 的完整 功能面时,请使用该技能;当它没有 shell 时,或者当你希望在引擎运行之前 验证类型化参数时,请使用此服务器。
开发
npm install
npm test # typecheck, lint, build, and the full suite
npm run test:watch欢迎贡献 —— 请参阅 CONTRIBUTING.md。设计 理由,包括被否决的备选方案,见 docs/rfc.md。
许可证
MIT。请参阅 LICENSE。
Available Tools
4 toolslist_formatsList supported formatsARead-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.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
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.
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.
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.
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.
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.
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 formatARead-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.
| Name | Required | Description | Default |
|---|---|---|---|
| detail | No | compact (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. | |
| format | Yes | A format profile from list_formats, such as "pdf", "docx", "xlsx", "pptx", "doc", "xls", "ppt", "key", "numbers", or "pages". |
TDQS
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.
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.
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.
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.
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.
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 documentARead-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.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Path to the document. The filename extension selects the format driver, and the container is then verified against it. | |
| view | No | report: full evidence — value, confidence, path, and cost per target. values: a compact target-to-value map. | |
| level | No | Probe budget and eligible paths. header: identity only. metadata (default). deep: higher-cost paths, needed only when a target's min_level says so. | |
| budget | No | Override the level's resource limits. Raise after a BUDGET_EXCEEDED error. | |
| targets | No | Short 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_confidence | No | Weakest evidence a path may offer. Default high; lower it to accept an approximation. | |
| target_confidence | No | Per-target override, e.g. {"slide_count": "exact"} to force the authoritative path. |
Output Schema
| Name | Required | Description |
|---|---|---|
| status | No | |
| schema_version | No |
TDQS
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.
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.
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.
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.
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.
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 documentsARead-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.
| Name | Required | Description | Default |
|---|---|---|---|
| view | No | report: full evidence — value, confidence, path, and cost per target. values: a compact target-to-value map. | |
| level | No | Probe budget and eligible paths. header: identity only. metadata (default). deep: higher-cost paths, needed only when a target's min_level says so. | |
| paths | Yes | Document paths, at most 64 per call. Literal paths only. | |
| budget | No | Override the level's resource limits. Raise after a BUDGET_EXCEEDED error. | |
| targets | No | Short 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_confidence | No | Weakest evidence a path may offer. Default high; lower it to accept an approximation. |
Output Schema
| Name | Required | Description |
|---|---|---|
| reports | Yes | One entry per requested path, in order. A per-file failure is confined to it. |
TDQS
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.
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.
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.
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.
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.
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.
4 tool updates
v0.1.1- First observed
list_formats - First observed
list_targets - First observed
probe - First observed
probe_batch
TDQS
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.
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.
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.
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
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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