Agent-Native Calendar
Agent-Native Google Calendar - manage events, sync, and public booking
Beschreibung vom Entwickler (englisches Original)
Read PDF internals: text, structure, fonts, signatures and tags, with what was not read declared.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"pdf-reader": {
"command": "npx",
"args": [
"-y",
"@shuji-bonji/pdf-reader-mcp"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add pdf-reader -- npx -y @shuji-bonji/pdf-reader-mcpIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"pdf-reader": {
"command": "npx",
"args": [
"-y",
"@shuji-bonji/pdf-reader-mcp"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"pdf-reader": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@shuji-bonji/pdf-reader-mcp"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 8. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto shuji-bonji bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.22.0) kam gestern in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Node.js auf deinem Computer.
In derselben Kategorie: Agent-Native Calendar, Excel MCP Server, MCP Server for Excel
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
Agent-Native Google Calendar - manage events, sync, and public booking
Create and edit Excel files with AI: charts, PivotTables, formulas. No Excel needed.
Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
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-reNur der Anfang wird gezeigt; den Rest findest du im Repo