Ermöglicht es AI Agents, PDF-Dokumente mithilfe einer performanten, auf Rust basierenden Library zu generieren, zu parsen, zu splitten, zu mergen und zu manipulieren.
Auch bekannt als bzsanti/oxidize-python, oxidize-python, oxidize-pdf
- Stars
- 6
- Tools
- 13
- Downloads, 30 Tage
- 4.005
- Neueste Version
- 0.23.0
- Letzter Commit
- 13. Nov. 2026
- Lizenz
- MIT
Was ist oxidize-pdf MCP?
oxidize-pdf ist ein MCP server. Ermöglicht es AI Agents, PDF-Dokumente mithilfe einer performanten, auf Rust basierenden Library zu generieren, zu parsen, zu splitten, zu mergen und zu manipulieren. Er stellt 13 Tools bereit, etwa read_pdf, extract_text, convert_pdf.
Zusammenfassung generiert aus dem README des Projekts
Über oxidize-pdf MCP server
Der oxidize-pdf MCP server bietet AI Agents eine performante Möglichkeit, mit PDF-Dokumenten zu interagieren. Er basiert auf einem Rust-Core und ermöglicht native Geschwindigkeit, ohne dass schwere C- oder Java-Abhängigkeiten erforderlich sind. Entwickler können diesen Server nutzen, um Agents die Fähigkeit zu geben, neue Dokumente zu generieren, bestehende zu parsen oder komplexe Manipulationen wie das Splitten, Mergen und Rotieren von Seiten durchzuführen.
Der Server läuft lokal über stdio und ist damit kompatibel mit Claude Desktop, GitHub Copilot in VS Code und dem OpenAI Agents SDK. Nutzer konfigurieren die Umgebung über ein OXIDIZE_WORKSPACE Verzeichnis, das als Sandbox für alle PDF-Operationen dient. Er enthält integrierte Sicherheitslimits wie OXIDIZE_MAX_FILE_SIZE_MB und OXIDIZE_MAX_PAGES, um die Verarbeitung von zu großen oder bösartigen Dateien zu verhindern.
Durch 12 spezialisierte Tools können Agents alles erledigen – von einfacher Textextraktion und dem Lesen von Metadaten bis hin zu fortgeschrittenen Aufgaben wie der Verwaltung von Formularfeldern, dem Hinzufügen von Annotationen und der Verifizierung digitaler Signaturen. Er unterstützt zudem die Konvertierung von PDFs in RAG-optimierte Formate oder Markdown, um Workflows zur Dokumentenanalyse zu unterstützen.
Was du damit machen kannst
- 1Text für Analysen extrahierenEin AI Agent kann Text aus spezifischen Seiten eines Dokuments extrahieren, um dessen Inhalt zusammenzufassen.
- 2Dokumentenstruktur ändernEin Entwickler kann einen Agent anweisen, mehrere Dateien zu kombinieren oder eine einzelne Datei in einzelne Seiten aufzuteilen.
- 3Daten für RAG vorbereitenEin Agent kann ein Standard-PDF in ein Format umwandeln, das für Retrieval-Augmented Generation optimiert ist.
- 4Formularverarbeitung automatisierenEine KI kann genutzt werden, um Daten in PDF-Formularfeldern programmatisch auszufüllen oder zu validieren.
- 5Dokumentensicherheit verifizierenEin Agent kann prüfen, ob ein PDF verschlüsselt ist, oder dessen digitale Signaturen verifizieren.
Geschrieben aus dem README des Projekts. Jeder Use Case wurde gegen ein Zitat daraus geprüft.
So installierst du oxidize-pdf MCP
Formate geprüft am 10. Nov. 2026oxidize-pdf MCP in Claude Code installieren
$ claude mcp add oxidize-python -- uvx oxidize-pdfoxidize-pdf MCP in Cursor installieren
~/.cursor/mcp.json
{
"mcpServers": {
"oxidize-python": {
"command": "uvx",
"args": [
"oxidize-pdf"
]
}
}
}oxidize-pdf MCP in VS Code installieren
.vscode/mcp.json
{
"servers": {
"oxidize-python": {
"type": "stdio",
"command": "uvx",
"args": [
"oxidize-pdf"
]
}
}
}oxidize-pdf MCP in Claude Desktop installieren
claude_desktop_config.json
{
"mcpServers": {
"oxidize-python": {
"command": "uvx",
"args": [
"oxidize-pdf"
]
}
}
}oxidize-pdf MCP in Codex installieren
~/.codex/config.toml
[mcp_servers.oxidize-python] command = "uvx" args = ["oxidize-pdf"]
oxidize-pdf MCP in Gemini CLI installieren
~/.gemini/settings.json
{
"mcpServers": {
"oxidize-python": {
"command": "uvx",
"args": [
"oxidize-pdf"
]
}
}
}oxidize-pdf MCP tools 13
Erkannt aus dem READMEread_pdfextract_textconvert_pdfcreate_pdfsave_pdfadd_contentannotate_pdfmanipulate_pdfmanage_formssecure_pdfextract_entitiesanalyze_pdf
| read_pdf | — | |
| extract_text | — | |
| convert_pdf | — | |
| create_pdf | — | |
| save_pdf | — | |
| add_content | — | |
| annotate_pdf | — | |
| manipulate_pdf | — | |
| manage_forms | — | |
| secure_pdf | — | |
| extract_entities | — | |
| analyze_pdf | — |
Alle 13 Tools anzeigenWeniger Tools anzeigen
add_pdf_content
| add_pdf_content | — |
Konfiguration
OXIDIZE_WORKSPACE
| Name | Beschreibung | Typ |
|---|---|---|
| OXIDIZE_WORKSPACE | — |
Automatisierte Checks
Geluften am 12. 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 erreichbarBestanden
- Open Source Lizenz (OSI)Bestanden
- Commit oder Release im letzten JahrBestanden
- Package-Name ähnelt keinem populären PackageBestanden
- Remote Endpoint nutzt HTTPSNicht geprüft
- Destruktive Tools sind markiertBestanden
- Keine versteckten Anweisungen an das ModellBestanden
- Kein kritischer Hinweis im Paket oder seinen AbhängigkeitenBestanden
README
Auf GitHub ansehenoxidize-pdf
Documentation · Context7 · Documentation publishing and indexing
Version 0.23.4 pins Rust core 5.5.6. See compatibility and validation.
Rust-powered PDF library for Python. Generate, parse, split, merge, and manipulate PDFs with native performance. Ships with a built-in MCP server so AI agents can work with PDFs out of the box.
No C dependencies. No Java. No subprocess calls.
Installation
pip install oxidize-pdf # Core library
pip install "oxidize-pdf[mcp]" # + MCP server for AI agents
Platforms: Linux (x86_64, aarch64) | macOS (x86_64, Apple Silicon) | Windows (x86_64) Requires: Python 3.10+
Version 0.23.4 pins Rust core 5.5.6, using the MIT-licensed oxidize-webpki
RustCrypto provider for certificate verification. See the
dependency policy for supported builds and limits.
0.23.4 release notes describe the signed-field permission fixes.
New APIs include explicit text recovery, non-breaking-space normalization,
build identification controls and incremental signature slots. See the
API guide and validation.
The current develop branch contains post-release parity work. See the current capability inventory and Python/.NET comparison for the audited subset, missing bindings and inherited core limitations. Neither the core version nor the type stubs establish full functional parity; no global coverage percentage is claimed.
Why oxidize-pdf?
| oxidize-pdf | Pure-Python libs | C/Java wrappers | |
|---|---|---|---|
| Performance | Native (compiled Rust) | Interpreted | Native but heavy |
| Dependencies | Zero | Varies | Poppler, Java, Ghostscript |
| Memory safety | Rust ownership model | GC-dependent | Manual / GC |
| Type stubs | Public API inventory + strict mypy checks on develop | Varies | Varies |
| AI-ready (MCP) | Built-in | No | No |
MCP Server
Expose the supported PDF tools to your AI agent:
oxidize-mcp
The built-in Model Context Protocol server exposes 12 tools, 5 static resources plus a session resource template, and 5 prompts over stdio. Install oxidize-pdf[mcp] to include its dependencies; the base library keeps MCP optional.
Version 0.20 uses FastMCP 4 and MCP Python SDK 2, with support for both modern and legacy stdio clients. See the migration guide for versions and installation routes.
If tools/list returns an empty array with an older installation (issue #198), upgrade to 0.20.0 or newer. These versions fix tool registration when starting server.py directly. On Windows, use the same Python environment for installation and startup:
python -m pip install --upgrade "oxidize-pdf[mcp]"
python -m oxidize_pdf.mcp.server
For a custom JSON-RPC client, send initialize, wait for its response, then send notifications/initialized before tools/list. Read newline-delimited JSON-RPC from stdout and keep stderr separate; the startup banner is written to stderr.
Claude Desktop integration
Add to your claude_desktop_config.json:
{
"mcpServers": {
"oxidize-pdf": {
"command": "oxidize-mcp",
"env": {
"OXIDIZE_WORKSPACE": "/path/to/your/pdfs"
}
}
}
}
GitHub Copilot (VS Code) integration
Copilot's agent mode speaks MCP. Add .vscode/mcp.json to your workspace:
{
"servers": {
"oxidize-pdf": {
"command": "oxidize-mcp",
"env": {
"OXIDIZE_WORKSPACE": "/path/to/your/pdfs"
}
}
}
}
Open the Chat view, switch to Agent mode, and the 12 PDF tools appear in
the tool picker. (The same block also works under the mcp.servers key in your
user settings.json if you prefer a global install.)
OpenAI Agents SDK integration
The OpenAI Agents SDK spawns the server over stdio and exposes its tools to an agent:
from agents import Agent, Runner
from agents.mcp import MCPServerStdio
async with MCPServerStdio(
params={"command": "oxidize-mcp", "env": {"OXIDIZE_WORKSPACE": "/path/to/your/pdfs"}},
cache_tools_list=True,
) as server:
agent = Agent(
name="PDF assistant",
instructions="Use the oxidize-pdf tools to inspect and manipulate PDFs.",
mcp_servers=[server],
)
result = await Runner.run(agent, "How many pages does report.pdf have?")
print(result.final_output)
A runnable version is in examples/openai_agents_quickstart.py.
Both integrations run the server locally over stdio, so its tools operate on PDFs in the configured workspace directory. This package does not expose a hosted HTTP endpoint. ChatGPT web needs a remote connection; developer-mode testing can also use Secure MCP Tunnel with a local stdio server. No ChatGPT plugin is published by this migration.
Available tools
| Tool | What it does |
|---|---|
read_pdf |
Read metadata — page count, version, encryption status, title, author |
extract_text |
Extract text from all pages or a specific page |
convert_pdf |
Convert to markdown, chunks, or RAG-optimized format |
create_pdf |
Create a new PDF with optional metadata |
save_pdf |
Save a session to disk, with optional encryption |
add_content |
Add pages, text, and graphics to a session |
annotate_pdf |
Add text annotations and highlights |
manipulate_pdf |
Split, merge, rotate, extract pages, reverse, overlay |
manage_forms |
Create, fill, read, and validate form fields |
secure_pdf |
Encrypt, check permissions, verify signatures |
extract_entities |
Extract structured entities from pages |
analyze_pdf |
Validate structure, detect corruption, check PDF/A compliance |
The server also exposes resources (session data, capabilities, version info) and prompts (guided workflows for summarization, data extraction, form filling, and more).
Configuration
OXIDIZE_WORKSPACE=/path/to/pdfs oxidize-mcp
The server is configured entirely through environment variables:
| Variable | Default | Purpose |
|---|---|---|
OXIDIZE_WORKSPACE |
~/Documents/oxidize-mcp |
Sandbox root; all paths must resolve inside it. |
OXIDIZE_ALLOWED_PATHS |
(none) | Comma-separated extra directories allowed outside the workspace. |
OXIDIZE_MAX_FILE_SIZE_MB |
100 |
Reject input PDFs larger than this on disk. |
OXIDIZE_MAX_PAGES |
10000 |
Reject documents with more pages than this before any extraction work. |
OXIDIZE_MAX_OUTPUT_BYTES |
10485760 |
Cap the serialized size of a tool's JSON response (10 MB). |
OXIDIZE_MAX_SESSIONS |
10 |
Maximum concurrent stateful PDF-creation sessions. |
OXIDIZE_MAX_SESSION_BYTES |
10485760 |
Cap the content a single session may accumulate (10 MB). |
OXIDIZE_SESSION_TIMEOUT |
3600 |
Session expiry, in seconds. |
Resource caps (OXIDIZE_MAX_*) protect the server from a large or malicious
PDF: oversized documents are rejected up front and tool responses are bounded
rather than serialized unbounded. Exceeding a cap returns an error with code
RESOURCE_LIMIT.
Or start programmatically:
from oxidize_pdf.mcp.server import run
run()
Python API
Create a PDF
from oxidize_pdf import Document, Page, Font, Color
doc = Document()
doc.set_title("My Document")
doc.set_author("Jane Doe")
page = Page.a4()
page.set_font(Font.HELVETICA, 24.0)
page.set_text_color(Color.black())
page.text_at(72.0, 750.0, "Hello from oxidize-pdf!")
page.set_font(Font.TIMES_ROMAN, 12.0)
page.text_at(72.0, 700.0, "Generated with Python + Rust.")
doc.add_page(page)
doc.save("output.pdf")
Parse an existing PDF
from oxidize_pdf import PdfReader
reader = PdfReader.open("document.pdf")
print(f"Pages: {reader.page_count}, Version: {reader.version}")
for i, text in enumerate(reader.extract_text()):
print(f"--- Page {i + 1} ---")
print(text)
Inspect tagged PDF structure
from pathlib import Path
from oxidize_pdf import TaggedPdfLimits, TaggedPdfValidationOptions, validate_tagged_pdf
report = validate_tagged_pdf(
Path("input.pdf").read_bytes(),
TaggedPdfValidationOptions(TaggedPdfLimits(max_depth=64)),
)
for finding in report.findings:
print(finding.severity, finding.code, finding.path, finding.message)
The report includes structure elements, artifacts, role/class maps, the parent
number tree and content MCIDs. Original dictionary values remain typed
PdfValue objects, including unknown attributes and reference generations.
Results are immutable snapshots; returned lists and dictionaries are owned copies.
valid means the core validator found no error-level findings. It is not a
PDF/UA certificate: an untagged PDF can have tagged=False, valid=True and a
MissingStructureTree warning. Malformed input raises PdfParseError, locked
input raises PdfEncryptionError, and exceeded validation budgets raise PdfError.
TaggedPdfLimits bounds visited objects, traversal depth, entries and decoded
content bytes (defaults: 100,000; 256; 1,000,000; 256 MiB). These are core validator
budgets, not a process memory or time limit: input copying and initial PDF parsing
occur before traversal. No PDF bytes are modified.
Operations
from oxidize_pdf import split_pdf, merge_pdfs, rotate_pdf, extract_pages
split_pdf("input.pdf", "output_dir/") # Split into individual pages
merge_pdfs(["part1.pdf", "part2.pdf"], "merged.pdf") # Merge multiple PDFs
rotate_pdf("input.pdf", "rotated.pdf", 90) # Rotate all pages
extract_pages("input.pdf", "subset.pdf", [0, 2, 4]) # Extract specific pages
Graphics
from oxidize_pdf import Document, Page, Color
doc = Document()
page = Page.a4()
page.set_fill_color(Color.hex("#3498db"))
page.draw_rect(72.0, 700.0, 200.0, 100.0)
page.fill()
page.set_stroke_color(Color.red())
page.set_line_width(2.0)
page.draw_circle(300.0, 500.0, 50.0)
page.stroke()
doc.add_page(page)
doc.save("graphics.pdf")
Types
from oxidize_pdf import Color, Point, Rectangle, Margins, Font
# Colors
Color.rgb(1.0, 0.0, 0.0) # RGB
Color.hex("#ff6600") # Hex
Color.cmyk(0.0, 1.0, 1.0, 0.0) # CMYK
# Geometry
Point(72.0, 720.0)
Rectangle.from_xywh(72.0, 72.0, 468.0, 648.0)
Margins.uniform(72.0)
# Fonts — all 14 standard PDF fonts
Font.HELVETICA # Font.HELVETICA_BOLD
Font.TIMES_ROMAN # Font.TIMES_BOLD
Font.COURIER # Font.COURIER_BOLD
Error handling
from oxidize_pdf import PdfReader, PdfError, PdfIoError, PdfParseError
try:
reader = PdfReader.open("missing.pdf")
except PdfIoError as e:
print(f"I/O error: {e}")
except PdfParseError as e:
print(f"Parse error: {e}")
except PdfError as e:
print(f"PDF error: {e}")
Exception hierarchy: PdfError > PdfIoError, PdfParseError, PdfEncryptionError, PdfPermissionError
MCP Server
oxidize-pdf includes an MCP server that exposes PDF capabilities to AI assistants like Claude. Install with the mcp extra:
pip install oxidize-pdf[mcp]
Claude Desktop
Add this to your claude_desktop_config.json:
{
"mcpServers": {
"oxidize-pdf": {
"command": "uvx",
"args": ["--from", "oxidize-pdf[mcp]", "oxidize-mcp"]
}
}
}
Claude Code
claude mcp add oxidize-pdf -- uvx --from "oxidize-pdf[mcp]" oxidize-mcp
Available tools
| Tool | Description |
|---|---|
read_pdf |
Open a PDF and get metadata (pages, version, encryption) |
extract_text |
Extract text content from PDF pages |
convert_pdf |
Convert between PDF versions |
analyze_pdf |
Analyze structure, fonts, images, and compliance |
extract_entities |
Extract images and digital signatures |
manipulate_pdf |
Split, merge, rotate, extract, and reorder pages |
annotate_pdf |
Add text annotations, highlights, and stamps |
manage_forms |
Create, fill, and read PDF form fields |
secure_pdf |
Encrypt, decrypt, and set document permissions |
create_pdf |
Create a new PDF document with pages |
add_pdf_content |
Add text, shapes, and images to pages |
save_pdf |
Save the document to file or bytes |
Resources
oxidize://fonts— Available built-in PDF fontsoxidize://page-sizes— Standard page sizes with dimensionsoxidize://capabilities— Server capabilities and tool listingoxidize://version— Version informationoxidize://workspace— PDF files in the workspace directoryoxidize://session/{id}— Session data by ID
Known limitations
- Encryption write support:
Document.encrypt()configures encryption parameters but the underlying Rust library does not yet serialize the encryption dictionary to the PDF output. Reading encrypted PDFs works correctly. - Image extraction returns raw embedded streams:
extract_images_from_pdfextracts each embedded image as-is (e.g. aDCTDecodeJPEG is written byte-for-byte). Image preprocessing — auto rotation-correction, contrast enhancement, denoise, upscaling, force-grayscale — is not available, because the build excludes the upstreamexternal-imagesfeature (and itsimage-crate dependency). This keeps extraction faithful and lossless; it does not silently return empty or stub results. - CPython only: PyPy and GraalPy are not supported.
License
MIT — see LICENSE for details.
Semantic comparison with revision history
from oxidize_pdf import (
compare_pdfs_semantically, SemanticComparisonLimits, SemanticComparisonOptions,
)
options = SemanticComparisonOptions(SemanticComparisonLimits(
max_objects=100_000, max_depth=256,
max_decoded_stream_bytes=256 * 1024 * 1024,
max_canonical_bytes=256 * 1024 * 1024,
max_extracted_text_bytes=64 * 1024 * 1024,
max_unreachable_objects=10_000, max_revisions=1024,
))
result = compare_pdfs_semantically(original_bytes, revised_bytes, options)
for difference in result.differences:
print(difference.path, difference.class_, difference.description)
for revision in result.right_revisions:
print(revision.index, revision.xref_offset, revision.semantic_fingerprint.hex())
for change in revision.object_changes:
print(change.object_number, change.generation, change.kind)
The immutable result exposes both revision histories, unreachable object
identities and pairs of semantically equivalent objects. Collection properties
return independent snapshots. Revision fingerprints are 32-byte hashes, and
revisions are ordered oldest first. class_ is the Python spelling of Rust's
class field. Difference classes are Visual, Textual, Structural, Metadata,
Security and SerializationOnly. semantically_equal may be true when the only
difference is SerializationOnly; it includes supported historical semantics,
so restoring the latest state does not erase an intervening semantic change.
Limits apply independently to each document. Decoded/canonical budgets count
work across repeated traversals, not just unique input bytes. Initial input
copies, parsing and some extraction allocations precede these checks; the
options are not process-wide memory/time limits. Malformed input, exceeded
budgets and unsupported decoding raise PDF errors; encrypted input raises
PdfPermissionError and must be decrypted before comparison.
This API compares the core's supported object/text domains, not rendered pixels,
and does not certify signatures or irreversible redaction. Core 5.4.2 includes
physical ObjStm/XRef containers among objects unreachable from Root/Info. A
qpdf conversion to object streams can therefore report Structural differences
at /UnreachableObjects and /Revisions despite equal text and page content.
The binding preserves that conservative result; it does not promise equivalence
across every PDF layout. The existing compare_pdfs API remains available.
Images from pixel buffers
from oxidize_pdf import Image, ImageColorSpace
rgb = Image.from_raw_data(b'\xff\x00\x00', 1, 1, ImageColorSpace.DeviceRGB)
gray = Image.from_gray_data(b'\x80', 1, 1)
rgba = Image.from_rgba_data(b'\xff\x00\x00\x80', 1, 1)
assert rgba.alpha_data == b'\x80'
assert rgba.soft_mask.data == b'\x80'
from_raw_data(data, width, height, color_space, bits_per_component=8) accepts
DeviceGray, DeviceRGB and DeviceCMYK. Components are packed in pixel order, most
significant bits first, with each scanline padded to a whole byte. Supported
component depths are 1, 2, 4, 8 and 16; 16-bit components use big-endian byte
order. RGBA and grayscale convenience constructors use 8-bit components.
All three constructors require positive dimensions and an exact buffer length.
Invalid sizes/depths raise ValueError; values outside unsigned argument ranges
raise OverflowError. The RGBA/gray constructors reject products exceeding
u32::MAX before calling the published core's dimension arithmetic. Validation
happens before copying the pixel buffer.
data, format, bits_per_component, alpha_data and soft_mask expose owned
snapshots. ImageFormat distinguishes Jpeg, Png, Tiff and Raw. Data is the core's
image payload: JPEG remains encoded, while PNG/TIFF constructors expose decoded
pixel data. RGBA separates RGB data from alpha; its soft mask can be inspected
independently. These APIs use the existing core without external-images or
new dependencies. Explicit mask creation/application and writer-object export
remain outside this increment.
Marked content on new pages
Page.begin_marked_content(tag) and
Page.begin_marked_content_with_actual_text(tag, actual_text) return a page-local
MCID. Pair every begin with Page.end_marked_content(); next_mcid() and
marked_content_depth() inspect the state. Tags are nonempty literal names
(UTF-8 bytes are PDF-name escaped, so pass "Span", not "/Span"). Empty tags
raise ValueError without changing state; ending an empty stack raises PdfError.
page = Page.a4()
page.set_font(Font.HELVETICA, 12)
mcid = page.begin_marked_content_with_actual_text("Span", "café 😀")
page.text_at(40, 700, "visible glyphs")
page.end_marked_content()
ActualText is a Unicode logical replacement; copying/extraction depends on the
viewer honoring it. For tagged structure, attach the returned ID using
StructureElement.add_mcid(page_index, mcid) and install the tree with
Document.set_struct_tree(tree). These operations alone do not certify PDF/UA.
The core writes these markers in the text context; they are intended for text
operations, not as a general scope around separately buffered graphics.
Coordinate transformations
TransformMatrix(a, b, c, d, e, f) exposes immutable affine components,
IDENTITY, translate, scale, rotate (radians), flip_y, multiply,
transform_point(Point) and to_pdf_ctm(). Composition a.multiply(b) applies
b first, then a. Values retain the core's floating-point semantics, including
singular and nonfinite matrices; validate them before using the CTM in a PDF.
from oxidize_pdf import CoordinateSystem, Point, TransformMatrix
matrix = TransformMatrix.translate(10, 20).multiply(TransformMatrix.scale(2, 3))
point = matrix.transform_point(Point(4, 5)) # Point(18, 35)
custom = CoordinateSystem.custom(matrix)
pdf_point = custom.to_pdf_standard(Point(4, 5), 800) # Point(18, 35)
CoordinateSystem supports point, Y-only and matrix conversions to PDF
coordinates, plus grows_upward(). For custom systems, Y-only conversion uses
x=0, orientation tests d > 0, and page height is ignored. Page.coordinate_system
returns a snapshot of the stored system. In core 5.4.2, setting this property
through set_coordinate_system does not automatically transform page content;
convert positions explicitly. LayoutManager remains outside this binding increment.
RenderContext(coordinate_system, page_width, page_height) stores mutable
coordinate_system, page_width, page_height and current_transform fields.
Its to_pdf_standard(Point) and y_to_pdf(y) methods use the current system and
height. The matrix is initialized from the constructor's system and height;
later field assignments do not recalculate it, and conversions do not read it.
This preserves core 5.4.2 behavior. Getters return independent value snapshots.
Use context.current_transform.transform_point(point) when you explicitly want
to apply the stored matrix. Numeric fields retain the core's f64 semantics.
Page.content_width and Page.content_height subtract the page margins.
Page.content_area returns (left, bottom, right, top) bounds in unrotated PDF
coordinates, rather than a position and size. These read-only properties reflect
current margins and can be negative or inverted when margins exceed page size.
Page.effective_width and Page.effective_height reflect rotation: 90°/270° swap
width and height. They use the full page dimensions, without subtracting margins.
Setting a coordinate system does not change these geometry properties.
Custom clipping paths
from oxidize_pdf import ClippingPath, WindingRule
clip = (ClippingPath().add_rect(10, 10, 80, 80)
.add_polygon([(30, 30), (70, 30), (50, 70)])
.with_winding_rule(WindingRule.EvenOdd))
page.set_clipping_path(clip)
move_to, line_to, curve_to, close_path and add_rect, add_circle,
add_ellipse, add_rounded_rect, add_polygon mutate and return the same path.
with_winding_rule returns an independent copy; the default is NonZero.
clear() removes commands while preserving the rule. is_empty reports whether
commands exist. Page.set_clipping_path retains a copy.
commands returns owned ClippingPathCommand snapshots with read-only kind
and copied coordinates: move/line use [x, y], cubic curves use two control
points and an endpoint [x1, y1, x2, y2, x3, y3], rectangles use
[x, y, width, height], and close has no coordinates. Coordinates are PDF user
space values; callers supply valid finite geometry. to_pdf_operations() emits
the core's clipping operators, including W/W* and n.
The existing rect, circle, and ellipse factories remain available.
This API does not expose path intersection, text clipping, or a clipping stack.
oxidize-pdf MCP Fragen
Wie füge ich oxidize-pdf MCP zu Claude Code hinzu?
Führe claude mcp add oxidize-python -- uvx oxidize-pdf in deinem Terminal aus. Füge --scope user hinzu, damit der Server in jedem Projekt verfügbar ist.
Wie füge ich oxidize-pdf MCP zu Cursor hinzu?
Öffne ~/.cursor/mcp.json und füge den Server unter mcpServers hinzu, mit der Cursor-Config aus dem Installationsabschnitt oben.
Welche Tools bietet oxidize-pdf MCP?
Er stellt 13 Tools bereit, darunter read_pdf, extract_text, convert_pdf, create_pdf, save_pdf.
Benötigt dieser Server externe Abhängigkeiten wie Java oder Poppler?
Nein, es ist eine auf Rust basierende Library ohne C-Abhängigkeiten, ohne Java und ohne Subprocess-Aufrufe.