Puter MCP
Puter MCP enables AI tools to interact with Puter: manage files, websites, workers, and more
作者提供的说明(英文原文)
Read PDF internals: text, structure, fonts, signatures and tags, with what was not read declared.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"pdf-reader": {
"command": "npx",
"args": [
"-y",
"@shuji-bonji/pdf-reader-mcp"
]
}
}
}在终端中运行这条命令
claude mcp add pdf-reader -- npx -y @shuji-bonji/pdf-reader-mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"pdf-reader": {
"command": "npx",
"args": [
"-y",
"@shuji-bonji/pdf-reader-mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"pdf-reader": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@shuji-bonji/pdf-reader-mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
依据这个服务器的连接方式和各应用自己的文档,检查于 2026年11月10日。
在你的电脑上运行,适用于
ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月10日
注册名称已通过 GitHub 账户 shuji-bonji 验证,该账户拥有此仓库
代码最后更新于前天
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 2 项适用的基础检查中通过了 2 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于前天,最新版本(0.23.0)于前天进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。
同一分类中有:Puter MCP, Agent-Native Slides, Agent-Native Forms
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Puter MCP enables AI tools to interact with Puter: manage files, websites, workers, and more
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
English | 日本語
An MCP (Model Context Protocol) server specialized in deciphering PDF internal structures.
While typical PDF MCP servers are thin wrappers for text extraction, this project focuses on reading and analyzing the internal structure of PDF documents. Pair it with pdf-spec-mcp for specification-aware structural analysis and validation.
| Server | Role |
|---|---|
| pdf-spec-mcp | PDF specification knowledge (ISO 32000, PDF/A, PDF/UA) |
| pdf-reader-mcp (this) | Read and inspect PDF internal structure — *what is in* a PDF |
| pdf-verify-mcp | Authenticity verification — *whether it is genuine*: cryptographic signature verification, tamper detection, PAdES level, PDF/A validation, encrypted-PDF decryption |
pdf-reader-mcp inspects signature structure (inspect_signatures); for cryptographic signature verification, trust/revocation evaluation, and PDF/A conformance validation, use pdf-verify-mcp.
18 tools organized into three tiers:
| Tool | Description | |
|---|---|---|
get_page_count | Lightweight page count retrieval | |
get_metadata | Full metadata extraction (title, author, PDF version...) | |
read_text | Text extraction with Y-coordinate reading order (opt-in `split_columns: 2 \ | 3 for untagged multi-column PDFs, compact_whitespace for Japanese forms). Resolves /ActualText replacements (§14.9.4, both the structure-element and the Span marked-content path). Reports **text extractability** per page (§9.10.1) so an empty result is never mistaken for an empty page. For **logical** order in tagged PDFs, prefer extract_structured_text` |
search_text | Full-text search with surrounding context. Searches the same text read_text returns, /ActualText included, so a hit means what a reader sees (a note names any page whose marked content could not be aligned) | |
read_images | Embedded image XObjects as PNG or JPEG files, returned as MCP image content blocks so a vision model can read them. max_width / max_height downscale by area average; the response has a byte budget and names anything it leaves out | |
read_url | Fetch a remote PDF and extract its text — nothing more. The bytes are not saved; to use the other 17 tools on a URL's PDF, download it first and pass the local path (see "read_url and the read-only boundary") | |
render_page | Rasterise pages to PNG/JPEG via PDFium-WASM (optional dependency @hyzyla/pdfium). The next step when text extractability says no_text_layer / not_extractable — draws the whole page, vector art and forms included | |
summarize | Quick overview report (metadata + text + image count + per-document text extractability) |
| Tool | Description |
|---|---|
inspect_structure | Object tree and catalog dictionary analysis |
inspect_catalog | Document-level inventory from the catalog (ISO 32000-2 §7.7.2): bookmarks (/Outlines), layers (/OCProperties), attachments (/EmbeddedFiles, with /AFRelationship), the XMP packet with its declared pdfaid / pdfuaid / W3C TDMRep (tdm:reservation) values, and what runs on open (/OpenAction, /AA, document-level JavaScript). Each entry says absent or unreadable — never one for the other. Declarations are reported as written, not verified |
inspect_tags | Tagged PDF structure tree visualization |
inspect_fonts | Font inventory (embedded/subset/type detection) |
inspect_annotations | Annotation listing (categorized by subtype) |
inspect_signatures | Digital signature field structure analysis |
extract_structured_text | Tagged PDF text in logical content order (ISO 32000-2 §14.8.2.5), each piece labelled with its structure type (H1 / P / Table …). Resolves /ActualText, separates /Alt and list labels, keeps page-spanning elements whole. include_bbox: true adds where each element is drawn — one rectangle per page, in the form add_annotation takes |
extract_tables | Tagged PDF subtree → Markdown table (preserves columns). A table continuing across a page break is ONE table (pages array) |
locate_objects | Object number → page and rectangle, in the coordinate form pdf-writer-mcp add_annotation takes. Bridges pdf-verify-mcp verify_integrity's "which objects changed" to "where they are". Each location names its basis: an annotation's own /Rect is exact, a content stream can only say "the whole page" |
| Tool | Description |
|---|---|
compare_structure | Structural diff between two PDFs (properties + fonts) |
validate_tagged and validate_metadata were removed (deprecated since 0.7.0). This server reports what a PDF contains and does not return pass/fail against a standard. For PDF/UA or PDF/A conformance, use pdf-verify-mcp validate_conformance (flavour: "pdfua-1", "pdfa-*", …). For the facts those tools used to look at, use inspect_tags (structure tree) and get_metadata (metadata fields) here.
read_url returns text, and only text. This is a decision, now stated rather than implied: the fetched bytes are discarded after extraction, because saving them would make a reader tool write to the file system, and every tool of this server is read-only (readOnlyHint: true — all 18 of them).
To run search_text, inspect_structure, extract_tables, render_page or anything else against a PDF that lives at a URL, download the file first — with whatever fetch capability the calling environment has — and pass the local path. Fetching is the caller's responsibility, deliberately: an agent environment always has a way to download a file, and a reader that also writes files has stopped being a pure observer.
read_url remains the right tool for the one-shot question: *what does the document at this URL say?*
summarize reporting hasText: false used to be a dead end: nothing in this server could read the document any further. render_page closes that — it rasterises pages to PNG or JPEG and returns them as MCP image content blocks, so a vision model can read a scan, a diagram, a filled form, or handwriting.
render_page({ file_path: "/path/to/scan.pdf", pages: "1-3", format: "jpeg" })
pages is required: rendering is the most expensive operation here, and "all pages" of a 500-page scan should be a decision, not a default. The same 4 MB response budget as read_images applies, with omissions named.
Rendering runs on PDFium compiled to WebAssembly (@hyzyla/pdfium, an optional dependency). A WASM binary is the same bytes on every platform, so the published package still behaves identically wherever npx runs it — the reason native addons are not used here. Without the dependency installed, render_page reports what to install and every other tool works normally. PDFium (BSD-3-Clause) is a different engine from the pdf.js this server reads text with; the tool description says so, because a rendering difference between engines must not be attributed to the file.
Measured before choosing this: pdf.js +
@napi-rs/canvas(1.0.7 and 0.1.80) segfaults the
whole process on pages that draw images — exactly the pages this tool exists for — and
renders blank pages when
standardFontDataUrlis not configured.
read_images used to base64 imgData.data — pdfjs's *decoded pixels*. An 8×8 RGB image was 192 bytes with no PNG or JPEG signature anywhere in it, so the result could not be opened by any viewer and could not be read by a vision model, which is the reason to extract an image in the first place.
Images are now encoded (PNG by default, lossless; format: "jpeg" with quality when smaller matters) and returned as MCP image content blocks, with the metadata alongside in a text block. Both encoders are written out here — no native addon, no per-platform binary.
The response is bounded at 4 MB of encoded image data. A 200 dpi A4 scan is ~11.6 MB of pixels on its own, so images past the budget are named with the reason rather than dropped:
read_images({ file_path: "/path/to/scan.pdf", pages: "1", max_width: 1200, format: "jpeg" })
read_images returns the image XObjects a page draws. It is not a picture of the page — vector drawings and text are not covered by it.
read_text used to answer with text or with nothing, and nothing meant three different things. ISO 32000-2 §9.10.1 separates them, so this server does too. Every text-returning tool — read_text, read_url, search_text, extract_structured_text, summarize — reports, per page:
| State | Condition | What to do next |
|---|---|---|
extracted | Every font used has a route to Unicode under §9.10.2 | Use the text |
no_text_layer | No text-showing operator (Tj TJ ' "), image content present | The page is pixels. OCR or a rendered image is needed; this server does neither |
not_extractable | A font used has no /ToUnicode, no standard encoding and no known CID collection | Text is missing or wrong. The report names the fonts and the clause |
not_observed | Encrypted, or the content stream could not be read | Nothing was measured. Not the same as "nothing is there" |
not_extractable is reported per font, so a page that mixes a readable font with an unreadable one is a partial loss and says so, rather than passing as complete.
The observation is made from the file, not from pdf.js's output: pdf.js synthesises a toUnicode map for every font it loads, so asking it whether a font has a /ToUnicode CMap answers yes for fonts whose dictionary has none.
npx @shuji-bonji/pdf-reader-mcp@latest
Add to your claude_desktop_config.json:
{
"mcpServers": { "pdf-reader-mcp": { "command": "npx", "args": ["-y", "@shuji-bonji/pdf-reader-mcp@latest"] } } }
Use `@latest`. The
-yflag innpx -yonly skips the install
prompt — it does not check for updates. Without
@latest, npx keeps
running whichever version it cached the first time, so new releases never
reach you. If you suspect you are on a stale version, run
rm -rf ~/.npm/_npxand restart your client.
claude mcp add pdf-reader-mcp -- npx -y @shuji-bonji/pdf-reader-mcp@latest
git clone https://github.com/shuji-bonji/pdf-re