# Brainiall Image Muse connector

From musedirectory.ai, the independent directory of Meta Muse connectors. Not affiliated with Meta.

## Brainiall Image

Remove backgrounds, upscale photos, restore faces, and extract text from documents.

- Record: https://musedirectory.ai/connector/brainiall-image
- Category: Productivity
- Developer: Brainiall (https://brainiall.com)
- Muse status: Extra setup. Not in Muse's Connectors list yet. Muse can still use it: its page gives you a request to paste into Muse.
- Health: Working, 1764ms, checked 2026-09-28T08:16:02Z
- Endpoint: https://api.brainiall.com/mcp/image/mcp
- Auth: No account needed; Pricing: unknown
- Screening: Screened, no issues found (2026-09-24T11:40:42Z)
- Source: Found in the official MCP Registry (com.brainiall/image) https://registry.modelcontextprotocol.io/v0/servers?search=com.brainiall%2Fimage

Connects to Brainiall's image processing engines. Muse can remove photo backgrounds, upscale images up to 4x, restore blurry or old faces, extract structured data from receipts and invoices, and convert documents to searchable text and markdown.

Example request: "Remove the background from a photo so I can use it as a profile picture."

How to connect: Not in Muse's Connectors list yet, but Muse can still use it. Paste this into Muse: "Use Brainiall Image to help me. It is a free service with an MCP server at https://api.brainiall.com/mcp/image/mcp. It does not need an API key. Ask me before you share anything with it." Muse asks before it shares anything with the app's site. Meta does not review apps used this way, so only use ones you trust. We tested this in the Muse app on September 24, 2026: Muse used an app's link directly this way and returned a live answer.

Tools:
- remove_background: Remove 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-encod
- upscale_image: Upscale 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_base
- restore_face: Restore 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
- check_image_service: Check 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_extract: Turn 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 (st
- document_query: Ask 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),
- document_tables: Reconstruct 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_markdown: Return 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_skillsets: Run 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_content: Multimodal 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.

Screening checks:
- MCP handshake: pass (Answered in 735ms)
- Domain against threat feeds (Cloudflare security DNS): pass (api.brainiall.com, brainiall.com not flagged)
- Published packages against the OSV malicious-package database: n/a (No npm or PyPI package published)
- Hidden instructions or invisible characters in tool text: pass (10 tools read, nothing found)
- Inputs asking for passwords, card numbers or seed phrases: pass (None found)
- Domain and redirects: pass (No redirects off the domain)
- AI review of purpose and tool behavior: pass (No concerns)