What can you do with this server?

This server provides OCR (Optical Character Recognition) processing capabilities, allowing you to submit documents and retrieve structured results. * Submit documents for OCR (parse_document): Upload a document via local file path, URL, or base64-encoded content; configure language, backend engine, page range, formula/table detection, and parse method; optionally wait for completion or submit asynchronously. * Check task status (get_task_status): Retrieve the current status and metadata of a submitted OCR task by its task ID. * Read extracted markdown (get_markdown): Page through a task's OCR result as markdown text using offset and max-length parameters, suitable for large documents. * Get structured content blocks (get_content_blocks): Retrieve paginated structured content blocks (text, tables, formulas) from a task's result, with optional filtering by page index. * Get full result summary (get_full_result): Fetch task metadata along with capped markdown and content blocks in a single call, best suited for smaller documents. * Reprocess a task (reprocess_task): Re-run OCR on an existing task with optional adjustments such as page rotation, different backend, language, or selected page indices. * List tasks (list_tasks): View and search all OCR tasks associated with the configured API key, with pagination support.

How do I use ocr-mcp?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@ocr-mcp Parse the document at https://example.com/report.pdf" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

ocr-mcp

by asharca

Overview Schema Related Servers Score Discussions

Python

Remote

OcrPlane CLI

Agent-friendly command line client for the OcrPlane/MineRU OCR API.

ocrplane-cli is the installable package and Docker image name. The installed command is ocrplane.

Features

Typer command line interface
Pydantic v2 input and output models
Rich human-readable terminal output
Stable --json output for agents
--dry-run request planning
Async submit plus polling and paginated result reads

Related MCP server: MCP Document Parse Tool

Requirements

Python 3.11+
An OcrPlane API base URL
An API key from OcrPlane

Online Install

Recommended install with uv:

uv tool install "git+https://github.com/asharca/ocrplane-cli.git"
ocrplane --help

Run once without installing:

uvx --from "git+https://github.com/asharca/ocrplane-cli.git" ocrplane --help

Upgrade later:

uv tool upgrade ocrplane-cli

Alternative isolated install with pipx:

pipx install "git+https://github.com/asharca/ocrplane-cli.git"
ocrplane --help

If the repository is private or you prefer SSH:

pipx install "git+ssh://git@github.com/asharca/ocrplane-cli.git"
ocrplane --help

Upgrade later:

pipx upgrade ocrplane-cli

Install into the current Python environment with pip:

python3 -m pip install "git+https://github.com/asharca/ocrplane-cli.git"
ocrplane --help

Run directly with Docker:

docker run --rm \
  -e OCRPLANE_BASE_URL="https://ocr.rhzy.ai" \
  -e OCRPLANE_API_KEY="mk_xxxxxxxxxxxxxxxxxxxx" \
  -v "$PWD:/workspace" \
  ghcr.io/asharca/ocrplane-cli:latest \
  parse /workspace/report.pdf --json

macOS Install

Using the system Python or Homebrew Python:

cd ~/Code/ocrplane-cli
python3 -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
python -m pip install -e .
ocrplane --help

If python3 is missing:

brew install python

Install with uv:

brew install uv
uv tool install "git+https://github.com/asharca/ocrplane-cli.git"
ocrplane --help

Or install uv with the official standalone installer:

curl -LsSf https://astral.sh/uv/install.sh | sh
uv tool install "git+https://github.com/asharca/ocrplane-cli.git"
ocrplane --help

Optional isolated install with pipx:

brew install pipx
pipx ensurepath
pipx install "git+https://github.com/asharca/ocrplane-cli.git"
ocrplane --help

Linux Install

Debian/Ubuntu:

sudo apt-get update
sudo apt-get install -y python3 python3-venv python3-pip git
cd ~/code/ocrplane-cli
python3 -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
python -m pip install -e .
ocrplane --help

RHEL/CentOS/Fedora:

sudo dnf install -y python3 python3-pip git
cd ~/code/ocrplane-cli
python3 -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
python -m pip install -e .
ocrplane --help

Optional isolated install with pipx:

python3 -m pip install --user pipx
python3 -m pipx ensurepath
pipx install "git+https://github.com/asharca/ocrplane-cli.git"
ocrplane --help

Install with uv:

curl -LsSf https://astral.sh/uv/install.sh | sh
uv tool install "git+https://github.com/asharca/ocrplane-cli.git"
ocrplane --help

Run once with uvx:

uvx --from "git+https://github.com/asharca/ocrplane-cli.git" ocrplane --help

Configure

Set the API endpoint and key:

export OCRPLANE_BASE_URL="https://ocr.rhzy.ai"
export OCRPLANE_API_KEY="mk_xxxxxxxxxxxxxxxxxxxx"

Compatibility aliases are also supported:

MINERU_API_BASE_URL
MINERU_BASE_URL
MINERU_API_KEY
API_KEY
APIKEY

Prefer OCRPLANE_BASE_URL and OCRPLANE_API_KEY for new setups.

To keep local secrets out of git:

cp .env.example .env

Then edit .env and load it before using the CLI:

set -a
source .env
set +a

Quick Start

Validate a request without sending it:

ocrplane parse /workspace/report.pdf --json --dry-run

Submit a document and wait for completion:

ocrplane parse /workspace/report.pdf --json

For large documents, submit first and read results by page:

ocrplane parse /workspace/large.pdf --json --no-wait
ocrplane status <task_id> --json
ocrplane markdown <task_id> --json --offset 0 --max-length 12000
ocrplane blocks <task_id> --json --offset 0 --limit 50

Write result artifacts to disk:

ocrplane parse /workspace/report.pdf --save-dir /workspace/ocr-report

This writes:

summary.json
result.md
content_blocks.json
pages.json

Commands

ocrplane parse FILE
ocrplane status TASK_ID
ocrplane markdown TASK_ID
ocrplane blocks TASK_ID
ocrplane result TASK_ID
ocrplane list
ocrplane reprocess TASK_ID
ocrplane settings

Common parse options:

ocrplane parse /workspace/a.pdf \
  --backend pipeline \
  --lang ch \
  --parse-method auto \
  --formula \
  --table \
  --start-page 0 \
  --end-page 9 \
  --timeout 900 \
  --poll-interval 3 \
  --json

Docker

Build locally:

docker build -t ocrplane-cli .

Run against a mounted workspace:

docker run --rm \
  -e OCRPLANE_BASE_URL \
  -e OCRPLANE_API_KEY \
  -v "$PWD:/workspace" \
  ocrplane-cli parse /workspace/report.pdf --json

Published images use:

ghcr.io/asharca/ocrplane-cli:latest

The GitHub Actions workflow publishes this image on pushes to main.

Agent Notes

Use --json for machine-readable output.
Use --dry-run when planning a call or checking paths.
Use --no-wait for large files, then poll with status.
Read large markdown with markdown --offset --max-length.
Read structured OCR blocks with blocks --offset --limit.
Avoid printing API keys in logs or prompts.

Development

python3 -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
python -m pip install -e .
python -m compileall src/ocrplane
python -m pip wheel . --no-deps -w /tmp/ocrplane-cli-wheel

Install Server

license - not found

quality

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

–Release cycle

–Releases (12mo)

Commit activity

Resources

GitHub Repository

Need Help?

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