Konvertiert HTML und Markdown in PDF und extrahiert Text, Bilder oder Markdown aus bestehenden PDF-Dokumenten.
Auch bekannt als Moonwalker1307/PdfPecker.Python, pdfpecker-python
- Stars
- 1
- Tools
- —
- Downloads, 30 Tage
- 1.098
- Neueste Version
- 1.25.0
- Letzter Commit
- 12. Nov. 2026
- Lizenz
- MIT
Was ist PdfPecker MCP?
PdfPecker ist ein MCP server. Konvertiert HTML und Markdown in PDF und extrahiert Text, Bilder oder Markdown aus bestehenden PDF-Dokumenten.
Zusammenfassung generiert aus dem README des Projekts
Über PdfPecker MCP server
PdfPecker ermöglicht es Entwicklern und KI-Agenten, HTML oder Markdown in professionelle PDF-Dokumente umzuwandeln. Dieser MCP server bietet eine extrem schnelle Methode, um Dokumente aus Code zu generieren oder relevante Inhalte aus bestehenden Dateien zu extrahieren. Er läuft lokal via stdio und benötigt keinen externen Browser, keine Systemabhängigkeiten und keine .NET-Installation, da die benötigte native Library direkt im Python-Package enthalten ist.
Nutzer können mit dem Server über spezifische Tools wie html_to_pdf, markdown_to_pdf und pdf_to_markdown interagieren. Er ist besonders nützlich für Agenten, die Dokumentenlayouts mittels render_pdf_pages visualisieren oder komplexe Dateien über pdf_to_text parsen müssen. Der Server wahrt die Sicherheit, indem er Dateioperaionen auf die bei der Einrichtung festgelegten Root-Ordner beschränkt. Da er eine eigene Layout-Engine anstelle eines schweren Browsers nutzt, kann er eine einseitige Rechnung in weniger als einer Millisekunde verarbeiten, was ihn hocheffizient für automatisierte Workflows macht.
Geschrieben aus dem README des Projekts. Jeder Use Case wurde gegen ein Zitat daraus geprüft.
So installierst du PdfPecker MCP
Formate geprüft am 10. Nov. 2026PdfPecker MCP in Claude Code installieren
$ claude mcp add pdfpecker-python -- uvx pdfpeckerPdfPecker MCP in Cursor installieren
~/.cursor/mcp.json
{
"mcpServers": {
"pdfpecker-python": {
"command": "uvx",
"args": [
"pdfpecker"
]
}
}
}PdfPecker MCP in VS Code installieren
.vscode/mcp.json
{
"servers": {
"pdfpecker-python": {
"type": "stdio",
"command": "uvx",
"args": [
"pdfpecker"
]
}
}
}PdfPecker MCP in Claude Desktop installieren
claude_desktop_config.json
{
"mcpServers": {
"pdfpecker-python": {
"command": "uvx",
"args": [
"pdfpecker"
]
}
}
}PdfPecker MCP in Codex installieren
~/.codex/config.toml
[mcp_servers.pdfpecker-python] command = "uvx" args = ["pdfpecker"]
PdfPecker MCP in Gemini CLI installieren
~/.gemini/settings.json
{
"mcpServers": {
"pdfpecker-python": {
"command": "uvx",
"args": [
"pdfpecker"
]
}
}
}Automatisierte Checks
Geluften am 14. Nov. 2026Vollständiger Bericht →Unsere automatisierten Checks bestanden. Das ist kein Security-Audit: Lies den Code und gib dem Server nur den minimal notwendigen Zugriff. Wie die Checks funktionieren
- Source Repository verknüpft und erreichbarmoonwalker1307/pdfpecker.python is public and reachablegithub.com/moonwalker1307/pdfpecker.python ↗Bestanden
- Paket nennt dieses Repository als Quellepdfpecker names https://github.com/Moonwalker1307/PdfPecker as its sourcepypi.org/project/pdfpecker/ ↗Befund
- Build-Herkunft (Sigstore-Attestierung)Sigstore attestation for pdfpeckerpypi.org/project/pdfpecker/ ↗Bestanden
- Open Source Lizenz (OSI)MITspdx.org/licenses/MIT.html ↗Bestanden
- Commit oder Release im letzten JahrLast commit or release 2026-11-12github.com/moonwalker1307/pdfpecker.python ↗Bestanden
- OpenSSF ScorecardNicht geprüft
- Package-Name ähnelt keinem populären PackageNo popular package one edit away from pdfpeckerBestanden
- Kein kritischer Hinweis im Paket oder seinen Abhängigkeitenthe package checked; no critical advisoryosv.dev ↗Bestanden
- Keine versteckten Anweisungen an das Modell0 tool descriptions and the README read; no override phrases, credential paths or hidden charactersBestanden
- Destruktive Tools sind markiertNicht geprüft
- Remote-Endpoint beantwortet den MCP-HandshakeNicht geprüft
README
Auf GitHub ansehenpdfpecker for Python
Fast HTML and Markdown to PDF, and PDF to images and text, for Python. No browser, no dependencies, no .NET to install.
pip install pdfpecker
import pdfpecker
pdf = pdfpecker.html_to_pdf("<h1>Invoice 42</h1><p>Total: <b>1,250.00 EUR</b></p>")
pdfpecker.html_file_to_pdf("templates/invoice.html", "invoice.pdf") # images and CSS resolve next to the file
pdfpecker.markdown_file_to_pdf("README.md", "readme.pdf")
pngs = pdfpecker.pdf_to_images(pdf, dpi=96) # one PNG per page (or format="jpeg"/"webp")
text = pdfpecker.pdf_to_text(pdf) # pages separated by \f
both = pdfpecker.merge_pdfs([pdf, "terms.pdf"])
This is the PdfPecker .NET library, compiled ahead of time into a native library that ships inside the wheel. PdfPecker has its own HTML parser, CSS engine, layout engine, PDF writer and PDF renderer, so a conversion takes about a millisecond for a one-page invoice and never starts a browser. The package version is the library version it holds. Documentation of what PdfPecker renders, its CSS support and its limitations: pdfpecker.net/docs.
Platforms
Wheels for Linux (glibc 2.28+ and musl, x86-64 and ARM64), macOS (Apple Silicon and Intel) and Windows (x64 and ARM64), on Python 3.9 and later. Each wheel is about 9 MB and has no Python or system dependencies.
Speed
From Python, on a 4-core Linux cloud VM, median time per document after warm-up; the documents are the benchmark pages of the PdfPecker repository:
| Invoice, 1 page | Feature tour, 5 pages | Report, 29 pages | Start-up and first PDF | Peak memory, one PDF | |
|---|---|---|---|---|---|
| pdfpecker | 0.7 ms | 2.9 ms | 32 ms | 57 ms | 32 MB |
| Chromium 153 via Playwright | 24 ms | 48 ms | 290 ms | 735 ms | 542 MB |
| xhtml2pdf 0.2.28 | 33 ms | 209 ms | 2.9 s | 453 ms | 63 MB |
| WeasyPrint 70.0 | 324 ms | 797 ms | 4.2 s | 1.1 s | 75 MB |
API
Every function takes bytes or a path for PDFs, raises a subclass of PdfPeckerError on failure, is thread-safe and
releases the GIL while it works, so threads convert in parallel.
| Function | Returns |
|---|---|
html_to_pdf(html, **options) |
PDF bytes from an HTML str or UTF-8 bytes |
html_file_to_pdf(path, output=None, **options) |
PDF bytes, also written to output when given; base_dir is the file's folder |
markdown_to_pdf(markdown, **options) |
PDF bytes from CommonMark with GitHub tables, task lists, strikethrough and footnotes |
markdown_file_to_pdf(path, output=None, **options) |
as html_file_to_pdf |
pdf_to_images(pdf, dpi=150, format="png", pages=None, width=None, height=None, transparent=False, quality=None, password=None) |
a list of encoded images, one per page |
pdf_to_text(pdf, pages=None, password=None, order="reading") |
the text in reading order, pages separated by \f; order="top_to_bottom" reads across columns as before 1.24.0 |
pdf_to_text_pages(pdf, pages=None, password=None, order="reading") |
a list with the text of each page |
pdf_to_markdown(pdf, pages=None, include_links=True, include_annotations=True, include_images=False, page_comments=False, max_pages=None, password=None) |
GitHub Flavored Markdown of any PDF: headings, lists and tables in reading order, for search indexes and language models |
pdf_page_count(pdf, password=None) |
the number of pages |
merge_pdfs(pdfs, title=None, author=None, bookmarks=True, creation_date=None) |
one PDF from several |
pdf_to_pdfa(pdf, output=None, conformance="PDF/A-2b") |
any PDF converted to PDF/A-2b, -2u, -3b or -3u, as a PdfAResult with pdf, changes, problems and is_conformant |
redact_pdf(pdf, output=None, text=None, pattern=None, areas=None, ignore_case=False, fill_color="#000000") |
any PDF with the matching text, or the (page, x, y, width, height) areas in points, removed from the file (text, image pixels, shapes, links and fields), not only covered |
read_barcodes(data, formats=None, try_inverted=True, pages=None, password=None, dpi=None) |
the QR, Data Matrix, Code 128 and EAN-13 codes in an image or the pages of a PDF, as Barcode objects with format, text, data, is_gs1, page, position and corners |
library_version() |
the version of the PdfPecker library inside |
pages takes a page number, a list of numbers, or a range such as "1-3,5", "8-" or "last", numbered from 1.
Every function also takes timeout in seconds.
Options of the HTML and Markdown functions:
| Option | Meaning |
|---|---|
base_dir |
The folder relative image, stylesheet and font paths resolve against. Without it, a document from a string loads no local files. |
allow_file_access |
Let the document read files outside base_dir too. Only for HTML you trust. |
page_size, landscape |
"A3", "A4" (default), "A5", "Letter", "Legal" or (width_mm, height_mm). A CSS @page { size } rule wins. |
margin |
In points (72 per inch): one number or (top, right, bottom, left). Default 36. CSS @page { margin } wins. |
scale, shrink_to_fit |
Zoom the content; shrink content wider than the page (on by default). |
header_text, footer_text |
A line of text in the top or bottom margin; {page} and {pages} are replaced. CSS margin boxes (@top-center, ...) do more. |
fonts, use_system_fonts |
TrueType/OpenType files or folders that CSS font-family can name; or look families up among the installed fonts. |
title, author, subject, keywords, language |
Document properties. |
user_style_sheet |
CSS applied after the document's own. |
creation_date |
A fixed date (datetime, date or Unix seconds): the output is then byte-identical from run to run. |
conformance |
"PDF/A-2b", "PDF/A-3b", "PDF/A-2u", "PDF/A-3u", "PDF/A-4" or "PDF/A-4f". |
accessibility |
"tagged", "PDF/UA-1" or "PDF/UA-2". |
compress, bookmarks, max_pages |
Compress streams (on); bookmarks from headings (on); stop beyond this many pages (100,000). |
Errors: PdfPeckerArgumentError (also a ValueError) for bad options, PdfReadError for input that is not a
readable PDF, PdfPasswordError, PdfLimitError for max_pages and the size limits, PdfTimeoutError (also a
TimeoutError) and PdfFileError (also an OSError) for a font or file that cannot be read.
Using it from AI agents and skills
pdfpecker suits code that an agent writes and runs in a sandbox: one pip install, nothing to download at run time,
no browser to launch, and errors that say what went wrong. A few things to tell the agent:
- Write the document as HTML with CSS; put page size, margins, page numbers and running headers in
@pagerules, for example@page { size: A4; margin: 20mm; @bottom-center { content: "Page " counter(page) " of " counter(pages) } }. - There is no JavaScript: charts must be SVG or images, not a script that draws them.
- Images, stylesheets and fonts load from
base_dir(ordata:URIs), never from the network. - The built-in fonts (Helvetica, Times and Courier, with bundled fallback fonts for the letters they lack) cover
Latin, Greek and Cyrillic; other scripts come out as question marks. For Chinese, Japanese, Arabic, Hebrew, Hindi or Thai, pass
fonts=[...]with a font that covers the script, oruse_system_fonts=True. - To check a result, render it back with
pdf_to_images(pdf, dpi=60)and look at the pages, or read it withpdf_to_text.
MCP server
The package includes a Model Context Protocol server, so chat apps and coding agents that speak MCP can make PDFs, look at their pages and read them. It runs over stdio and needs nothing but this package:
claude mcp add pdfpecker -- uvx pdfpecker mcp # Claude Code
For Claude Desktop and other apps that read an mcpServers setting:
{ "mcpServers": { "pdfpecker": { "command": "uvx", "args": ["pdfpecker", "mcp", "--root", "/Users/me/Documents/pdfs"] } } }
| Tool | What it does |
|---|---|
html_to_pdf |
HTML (inline or a file) to a PDF file, with previews of the first pages to check the layout |
markdown_to_pdf |
the same for Markdown |
render_pdf_pages |
PNG images of up to 20 pages, for the model to look at |
pdf_to_text |
the text of a PDF, page by page |
pdf_to_markdown |
any PDF as Markdown, returned or written to a file |
pdf_to_pdfa |
any PDF converted to PDF/A, with what changed and what could not be fixed |
pdf_info |
page count and file size |
merge_pdfs |
several PDF files into one |
The tools read and write files only inside the --root folders (repeatable), because the model picks the paths. The
default is the current folder, or ~/PdfPecker when the server starts in the filesystem's root, as chat apps often
do. python -m pdfpecker mcp runs the same server without uvx.
Building from source
The wheel's native library is built from the released PdfPecker NuGet package named in PDFPECKER_VERSION.
It needs the .NET 10 SDK with the NativeAOT prerequisites (clang on Linux, Xcode on macOS, the Visual Studio C++
tools on Windows):
ci/build.sh linux-x64 manylinux_2_39_x86_64 # RID and wheel tag; builds, packs and tests the wheel
Or by hand: dotnet publish native/PdfPecker.Native.csproj -c Release -r linux-x64, copy pdfpecker_native.so
(.dylib, .dll) into src/pdfpecker/, and run pytest. PDFPECKER_NATIVE_LIB points the package at a library
elsewhere.
The C ABI (native/Exports.cs) is one function, pdfpecker_invoke(op, input, input_len, options_json, &output, &output_len, &error), plus pdfpecker_free, pdfpecker_version and pdfpecker_abi_version, so other languages
with an FFI can use the same library.
Releasing
A PdfPecker release on NuGet is followed by a pull request here that changes PDFPECKER_VERSION. Once it is merged,
the owner publishes a GitHub release tagged v<version>; the Wheels workflow builds the eight wheels again, checks the
tag against PDFPECKER_VERSION and uploads them to PyPI with Trusted Publishing. It then lists the new version of
the MCP server (server.json) in the official MCP Registry.
License
MIT. The wheel also contains the .NET runtime, zlib-ng and the fonts and data PdfPecker bundles, each under its own
license: see THIRD-PARTY-NOTICES.md.
PdfPecker MCP Fragen
Wie füge ich PdfPecker MCP zu Claude Code hinzu?
Führe claude mcp add pdfpecker-python -- uvx pdfpecker in deinem Terminal aus. Füge --scope user hinzu, damit der Server in jedem Projekt verfügbar ist.
Wie füge ich PdfPecker MCP zu Cursor hinzu?
Öffne ~/.cursor/mcp.json und füge den Server unter mcpServers hinzu, mit der Cursor-Config aus dem Installationsabschnitt oben.
Wie geht PdfPecker mit Bildern und CSS in HTML-Dateien um?
Bilder, Stylesheets und CSS werden relativ zum Ordner der Datei aufgelöst, sofern die base_dir Option genutzt wird.
Ist der Server sicher für die Nutzung durch KI-Agenten in einer Sandbox?
Ja, er ist für Sandbox-Umgebungen konzipiert, da er nur ein pip install benötigt, keine Downloads zur Laufzeit durchführt und den Dateizugriff auf die festgelegten Root-Ordner beschränkt.