Brainiall Image

Background removal, upscaling, face restore, document OCR, table extraction, visual understanding.

CommunityDegradedNo sign-inGlobalFreeRead-only

What it can do

    What data it sees

    Do you need an account

    No: the server works without sign-in

    Background removal, upscaling, face restore, document OCR, table extraction, visual understanding.

    How to connect

    How to connect Brainiall Image to Claude

    The server address to paste into Claude settings:

    https://api.brainiall.com/mcp/image/mcp

    1. Open Claude (claude.ai or the desktop app).
    2. Go to Settings → Connectors.
    3. Click Add custom connector.
    4. Paste the server address copied below into Remote MCP server URL and click Add.
    5. In a chat, click + → Connectors and switch the new connector on.

    Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.

    Authorization

    After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.

    How to connect Brainiall Image to ChatGPT

    The server address to paste into ChatGPT settings:

    https://api.brainiall.com/mcp/image/mcp

    1. Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
    2. Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
    3. Open Settings → Connectors and click Create.
    4. Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
    5. Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
    6. In a new chat open + → Apps/Connectors and enable the connector.

    OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.

    Authorization

    On first use ChatGPT opens the service's sign-in window. Sign in and approve access.

    How to connect Brainiall Image to Cursor

    The server address to paste into Cursor settings:

    https://api.brainiall.com/mcp/image/mcp

    Fastest: click Open in Cursor below and confirm the prompt.

    Manually:

    1. In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
    2. Paste the JSON copied below into ~/.cursor/mcp.json (per project: .cursor/mcp.json in the repo root).
    3. Save the file. The server appears in the MCP list; authorize it there if asked.

    Authorization

    If the service needs sign-in, an authorize button appears next to the server in the MCP list.

    Server tool list (10)

    Raw names from tools/list. Only developers need these.

    remove_backgroundRemove the background from an image. Uses Brainiall Cutout engine segmentation to precisely separate foreground from background. Returns a base64-encoded image with transparent background (PNG) or white background (WebP). Sub-500ms latency on GPU. Args: image_base64: Base64-encoded image data (PNG, JPEG, or WebP). output_format: Output format -- 'png' (with transparency) or 'webp'. Returns: dict with keys: - image_base64 (str): Base64-encoded result image - format (str): Output image format - original_size (dict): Original width and height - processing_ms (int): Processing time in milliseconds
    upscale_imageUpscale image resolution with the Brainiall image-upscaling engine. Enhances image resolution by 2x or 4x with the GPU-accelerated Brainiall image-upscaling engine super-resolution. Processes in tiles (256x256) to manage VRAM. Maximum output dimension: 8192x8192. Args: image_base64: Base64-encoded image data (PNG, JPEG, or WebP). scale: Upscale factor -- 2 or 4 (default: 4). Returns: dict with keys: - image (str): Base64-encoded upscaled image - format (str): Output image format - width (int): Output width - height (int): Output height - scale (int): Scale factor applied - processing_time_ms (float): Processing time in milliseconds
    restore_faceRestore and enhance faces in an image with the Brainiall face-restoration engine. Detects all faces via RetinaFace, restores quality (fixes blur, noise, compression artifacts), and pastes them back. Optionally enhances the background with the Brainiall image-upscaling engine. GPU-accelerated, sub-3s latency. Args: image_base64: Base64-encoded image data containing faces (PNG, JPEG, WebP). upscale: Output upscale factor -- 1 to 4 (default: 2). enhance_background: Whether to enhance background with the Brainiall image-upscaling engine (default: true). Returns: dict with keys: - image (str): Base64-encoded restored image - format (str): Output image format - width (int): Output width - height (int): Output height - upscale (int): Scale factor applied - processing_time_ms (float): Processing time in milliseconds
    check_image_serviceCheck health status of Image API services and loaded models. Returns: dict with keys: - status (str): 'healthy' or error state - models (dict): Loaded model status per capability - version (str): API version
    document_extractTurn a document image into structured fields. doc_type picks the schema (receipt/invoice/id/contract/form/generic). A page with no readable text returns an error rather than a guess. Returns: dict with keys: doc_type (str), fields (dict — null for any value not present), text (str — the recognised plain text).
    document_queryAsk a natural-language question about a document image; returns a grounded answer plus the supporting line. Returns found:false rather than guessing when the document doesn't contain the answer. Returns: dict with keys: answer (str|null), found (bool), supporting_text (str|null), text (str).
    document_tablesReconstruct every table in a document image into headers and rows. Returns: dict with keys: table_count (int), tables (list of {title, headers, rows, row_count, column_count}); [] if there are no tables.
    document_to_markdownReturn the document as structured Markdown (headings, tables, lists, code blocks, math). Brainiall Doc Layout engine. The single API for converting documents to LLM-friendly format.
    run_skillsetsRun a multi-skill enrichment pipeline over a document image or text in one call. Brainiall Skillsets engine. Returns per-skill outputs ready for indexing or RAG.
    understand_contentMultimodal extraction. Send an image, text, or both; define your schema of fields; get structured JSON. Brainiall Content Understanding engine. Unified multimodal field extraction over images and text.