opencode-ppocr-mcp
DeepSeek Harness plugin and OpenCode MCP server: local PP-OCRv6 Medium OCR (PaddleOCR on ONNX Runtime, CPU) for images and multi-page PDFs. Exposes mcp__ppocr__ocr_image and mcp__ppocr__ocr_pdf.
- Stars
- 0
- Language
- JavaScript
- Created
- Aug 23, 2026
- Updated
- Oct 4, 2026
Introduction
opencode-ppocr-mcp
Local OCR, no cloud. PP-OCRv6 Medium detection + recognition on ONNX Runtime (CPU), for images and multi-page PDFs.
本地 OCR:PP-OCRv6 Medium 检测+识别,ONNX Runtime CPU 推理,可识别图片与多页 PDF。
As a DeepSeek Harness plugin: the MCP server ships inside the bundle, so
installing one plugin is the whole setup — no mcpServers file to hand-edit.
Install
DeepSeek Harness Desktop — open Plugins in the sidebar, choose Add plugin, and enter:
https://github.com/bauerelizabeth07139/opencode-ppocr-mcp
Then switch the new dsh-ppocr bundle on. The Desktop app boots the
reserved desktop profile, so that is where it has to be enabled.
dsh CLI — install it into the profile you actually boot:
dsh plugin --profile web add bauerelizabeth07139/opencode-ppocr-mcp
No git on the machine? pnpm resolves a git shorthand with git ls-remote,
which fails with 'git' is not recognized when git is missing. Use the tarball
instead — that path is plain HTTPS:
dsh plugin --profile web add https://codeload.github.com/bauerelizabeth07139/opencode-ppocr-mcp/tar.gz/main
The same address works in the Desktop Add plugin dialog. Replace main
with a commit SHA to pin an exact revision (/tar.gz/<sha>).
Uninstall with dsh plugin --profile web remove dsh-ppocr.
Requirements
-
Python ≥ 3.8 on
PATH, or pointed at withpython. -
The OCR stack in that interpreter — this is the heavy part:
pip install paddlepaddle==3.0.0 paddleocr==3.7.0 onnxruntime Pillowrequirements.txtin this repository pins exactly those. -
Disk and network for the first run: the detection and recognition models (~170 MB) download into
~/.paddlex/official_models/the first time a tool is called. CPU only; no GPU and no display.
Tools
The server registers 2 tool(s). DSH namespaces them automatically,
so the model calls them as mcp__ppocr__<tool>:
| Tool | What it does |
|---|---|
ocr_image | Runs detection + recognition on one image and returns the text. Parameter: image_path (required). |
ocr_pdf | Renders and recognises a PDF page by page. Parameters: pdf_path (required), start_page (default 1), end_page (optional). |
Configuration
| Key | Environment variable | Default | Meaning |
|---|---|---|---|
python | — | discovered | interpreter that runs the server — must have the OCR stack |
toolCallTimeoutMs | — | 600000 | DSH's per-call budget; the first call also downloads the models |
env | — | {} | raw environment passthrough (the server reads none) |
Every field is optional and lives in the loader row. For example, in
cordis.patch.yml:
- id: dsh-ppocr
name: 'dsh-ppocr'
config:
python: 'C:\ocr-venv\Scripts\python.exe'
toolCallTimeoutMs: 900000
Notes
- The plugin mounts; the interpreter must carry the stack. The server
imports PaddleOCR lazily, when a tool is called, so a missing dependency shows
up as a tool error naming the import rather than a plugin that refuses to
load. Point
pythonat an interpreter that haspaddlepaddle,paddleocr,onnxruntimeandPillow. - The first call is slow. Detection and recognition models (~170 MB)
download into
~/.paddlex/official_models/on first use; the 600 s per-call budget covers it. end_pagemust be a number. The server does not coerce it, so passing a string makes its comparison fail — pass an integer.
How it is mounted
index.js resolves a Python interpreter (the configured python, then
python3/python on PATH), hands the server its argv and working directory,
and mounts it as a stdio MCP server through @deepseek-ai/dsh-mcp-client with
failOnStartupError: true, so a server that cannot start is a visible error
rather than a silently missing tool.
Credentials are forwarded explicitly. The harness scrubs credential-shaped
variables (KEY, TOKEN, SECRET, PASSWORD) out of the environment a child
process inherits, so config.apiKey — falling back to the variable the server
documents — is written into the child's environment by the plugin itself. That
means both of these work:
config:
apiKey: '<your key>'
export the API key variable='<your key>' # picked up at load time
Development
No build step and no runtime dependencies — @deepseek-ai/cordis and
@deepseek-ai/dsh-mcp-client are peers supplied by the Harness.
npm test # node >= 22: manifest checks + the stdio mount, both Harness-free
The mount test loads index.js with @deepseek-ai/dsh-mcp-client stubbed and
asserts the exact stdio configuration the plugin produces, including the
credential forwarding above.
Repository layout
| Path | Purpose |
|---|---|
index.js | the DSH plugin: resolves the interpreter and mounts the server |
cordis.patch.yml | the loader row that activates the plugin |
locale/{en,zh}.json | card title and description for the plugin lists |
assets/icon.svg | card artwork |
test/ | npm test: manifest composition and the mount contract |
server.py | the MCP server, unchanged |
requirements.txt | the OCR stack, pinned |
Other hosts (unchanged)
The server is a plain stdio MCP server and still works anywhere else. The
repository's original README is kept verbatim as
README.opencode.md, and the launch stanza from it keeps
working:
{
"mcp": {
"ppocr": {
"type": "local",
"command": ["python", "path/to/server.py"],
"enabled": true
}
}
}
License
MIT — the repository's README declared MIT but shipped no licence file; this plugin's release adds one.