Yandex Vision OCR MCP

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A Model Context Protocol (MCP) server that exposes Yandex Vision OCR as tools, so any MCP-compatible client — opencode, Claude Desktop, Cursor, Cline — can extract text from images and PDFs.

Features

recognize_text — synchronous OCR for images (JPEG/PNG/WEBP/HEIC/HEIF) and single-page PDFs.
recognize_pdf — asynchronous OCR for PDFs (single- or multi-page) and large files,

via recognizeTextAsync + getRecognition polling.

Recognition models — printed text, multi-column, handwritten, tables,

Markdown, and math formulas (LaTeX), selectable per call.

Accepts a local file path or raw base64 content.
Recognition languages selectable between ru and en (default ru; combine as

["ru","en"] for mixed text). Auto-detect is not supported by this endpoint.

Three output formats: text (default), markdown, or full json (the raw

textAnnotation with blocks/lines/words/tables/entities).

Zero-touch error handling — API failures are returned as isError tool results, never crashes.
Lazy credentials — the server boots and lists tools even before YANDEX_* env vars are set,

surfacing a clear error only on the first call.

Prerequisites

Node.js ≥ 20.
A Yandex Cloud account with the Vision/OCR API enabled.
A folder ID + either an API key (recommended) or an IAM token.

See the authentication docs.

Quick start

# Run directly with npx (no install needed)
npx -y yandex-vision-ocr-mcp

Then wire it into your MCP client (see Configuration).

Configuration

The server reads credentials from environment variables:

| Variable | Required | Description | | -------------------- | -------- | ------------------------------------------------------------ | | YANDEX_FOLDER_ID | optional | Yandex Cloud folder ID. Only sent as x-folder-id when set — the API key already scopes requests, so you can usually leave this unset. If set, it must match the key's folder. | | YANDEX_API_KEY | one of | API key (recommended for long-lived usage). | | YANDEX_IAM_TOKEN | one of | Short-lived IAM token (~12h). Use instead of an API key. |

See .env.example for a template.

Models

Pass model to any tool to pick the recognition behaviour:

| Model | Best for | | ------------------- | ------------------------------------------------------------------------ | | page (default) | Single-column printed text. | | page-column-sort | Multi-column printed text. | | handwritten | Mixed handwritten + printed text (Russian, English). | | table | Tables (Russian, English). | | markdown | Printed text, also returned as Markdown. | | math-markdown | Math formulas, returned as Markdown with LaTeX (e.g. $a^2 + b^2$ ). |

Tip: use format: "markdown" together with the markdown / math-markdown models to receive the model's Markdown output directly.

Tools

Both tools accept the same input shape:

| Argument | Type | Default | Description | | ------------ | -------------------------- | ------- | --------------------------------------------------------------------------- | | path | string | — | Local file to OCR. Provide this or base64. | | base64 | string | — | Base64 content (data: URIs accepted). Provide this or path. | | mimeType | string | inferred | Explicit MIME type override. | | languages | string[] | ["ru"] | Recognition languages, selectable: ru, en (e.g. ["ru","en"] for mixed). | | model | string | page | Recognition model — see Models. | | format | text \| markdown \| json | text | Output format. |

Supported formats: JPEG, PNG, WEBP, HEIC, HEIF (images) and PDF. The mimeType sent to the API is derived automatically (you can pass a standard MIME type via mimeType if needed). BMP/TIFF are not supported by the service.

recognize_text — synchronous. Best for images and single-page PDFs.
recognize_pdf — asynchronous (submit + poll). Best for multi-page PDFs and large

files. Requires the input to be a PDF.

Example result (`text` format)

Hello World
Yandex OCR

Connect to opencode

Add the server to your opencode.json under mcp:

{
  "mcp": {
    "yandex-vision-ocr": {
      "type": "local",
      "command": ["npx", "-y", "yandex-vision-ocr-mcp@latest"],
      "enabled": true,
      "environment": {
        "YANDEX_FOLDER_ID": "b1g...",
        "YANDEX_API_KEY": "your-api-key"
      }
    }
  }
}

If you cloned the repo instead, replace the command with ["node", "/absolute/path/to/yandex-vision-ocr-mcp/build/index.js"].

Connect to Claude Desktop / Cursor / Cline

<details> <summary>Claude Desktop — <code>claude_desktop_config.json</code></summary>

{
  "mcpServers": {
    "yandex-vision-ocr": {
      "command": "npx",
      "args": ["-y", "yandex-vision-ocr-mcp@latest"],
      "env": {
        "YANDEX_FOLDER_ID": "b1g...",
        "YANDEX_API_KEY": "your-api-key"
      }
    }
  }
}

</details>

<details> <summary>Cursor — <code>.cursor/mcp.json</code></summary>

{
  "mcpServers": {
    "yandex-vision-ocr": {
      "command": "npx",
      "args": ["-y", "yandex-vision-ocr-mcp@latest"],
      "env": {
        "YANDEX_FOLDER_ID": "b1g...",
        "YANDEX_API_KEY": "your-api-key"
      }
    }
  }
}

</details>

Local development

git clone https://github.com/chupre/yandex-vision-ocr-mcp.git
cd yandex-vision-ocr-mcp
npm install
npm run build      # type-check + compile to build/
npm test           # run the vitest suite
npm run dev        # run the server from source via tsx
npm run inspector  # open the MCP Inspector UI against the build

Useful scripts:

| Script | Description | | ------------------- | -------------------------------------------- | | npm run build | Compile TypeScript to build/. | | npm run typecheck | Type-check without emitting. | | npm test | Run the offline test suite. | | npm run dev | Run the server from source (tsx). | | npm run inspector | Launch the MCP Inspector for manual testing. |

Testing

The offline suite covers input handling, MIME inference, response formatting, the HTTP client (via a fake transport, no network), tool wiring, and a full MCP round-trip over an in-memory transport.

Live integration tests hit the real Yandex OCR API and are skipped unless credentials and sample files are provided:

YANDEX_FOLDER_ID=... YANDEX_API_KEY=... \
YOCR_LIVE_IMAGE=./sample.png \
YOCR_LIVE_PDF=./sample.pdf \
npx vitest run tests/live.test.ts

Docker

docker build -t yandex-vision-ocr-mcp .
docker run --rm -i \
  -e YANDEX_FOLDER_ID=b1g... \
  -e YANDEX_API_KEY=... \
  yandex-vision-ocr-mcp

API coverage

This server targets the Yandex Cloud Vision OCR REST API (ocr.api.cloud.yandex.net/ocr/v1):

| Route | Method | Used for | | ---------------------- | ------ | ----------------------------------------- | | /recognizeText | POST | Synchronous recognition (recognize_text). | | /recognizeTextAsync | POST | Start async recognition (recognize_pdf). | | /getRecognition | GET | Poll for the async result. |

Concepts: OCR overview · image · PDF · handwritten.

License

MIT

yandex-vision-ocr-mcp