Brandfetch

Brandfetch MCP Server

The official Model Context Protocol server for Brandfetch. It gives AI assistants access to brand search, company data, logos and design assets, and LLM-ready brand context from the Brandfetch API.

• Learn more: https://brandfetch.com/developers/mcp
• Full documentation: https://docs.brandfetch.com/mcp/overview

Tools

Interactive brand card (MCP Apps)

On hosts that support the MCP Apps extension (claude.ai, Claude Desktop, ChatGPT, ...), get_brand results render as an interactive brand card: logo preview, format switcher (SVG/PNG/WebP/...), download and copy-URL actions. Hosts without Apps support fall back to the regular JSON tool result. get_brand_data returns the same brand data without the card, and get_brands fetches several brands in one call, so a logo wall of six brands is one batch call rather than six cards; the model picks between the three by their descriptions. The widget source lives in ui/ and is served by the server as the ui://brandfetch/brand-card.<hash>.html resource, named after a hash of the built file so ChatGPT fetches each new build.

Quick start (hosted server)

The easiest way to use this server is to connect to the Brandfetch-hosted endpoint — no install, no infrastructure:

https://mcp.brandfetch.io/mcp

Authentication uses a Brandfetch MCP token (a bf1. bearer token). Generate one from the Keys and MCP page in the Brandfetch dashboard, or connect via OAuth from a client that supports it.

Claude Desktop / Claude Code

{  "mcpServers": {    "brandfetch": {      "type": "http",      "url": "https://mcp.brandfetch.io/mcp",      "headers": {        "Authorization": "Bearer bf1.YOUR_TOKEN"      }    }  }}

Cursor

Add to ~/.cursor/mcp.json (or the project .cursor/mcp.json):

{  "mcpServers": {    "brandfetch": {      "url": "https://mcp.brandfetch.io/mcp",      "headers": {        "Authorization": "Bearer bf1.YOUR_TOKEN"      }    }  }}

ChatGPT

In ChatGPT, add a custom app (developer mode) with the server URL https://mcp.brandfetch.io/mcp and OAuth authentication, then sign in with your Brandfetch account.

Clients that support OAuth can instead point at https://mcp.brandfetch.io/mcp with no token and complete the authorization flow in the browser.

Quota errors

get_brand, get_brand_data, get_brands, enrich_transaction, and get_brand_context consume API credits from your plan; brand_search and build_logo_urls don't and keep working when your credits run out. get_brands uses one credit per brand it returns; every other result is free.

• 429 "API quota exhausted" — your key has used all of its API credits. Check usage or upgrade in the Brandfetch dashboard.
• 429 "Not enough API credits left for this batch" — get_brands asked for more brands than your key has credits left; nothing was charged. Ask for fewer brands.
• 403 "Batch lookups need a paid plan or prepaid credits" — get_brands is not available on the free plan; get_brand_data fetches the same brands one at a time.
• 403 "Forbidden" — the key has no available API credits or lacks access to that endpoint. The key itself may be valid, so check your plan and key status in the dashboard before rotating it.

Self-hosting

This is an HTTP (streamable-http) MCP server built with FastMCP. You can run your own instance with Docker.

docker build -t brandfetch-mcp-server .docker run --rm -p 8080:8080 brandfetch-mcp-server

The server then listens on http://localhost:8080/mcp. Point your MCP client at that URL and send your Brandfetch credentials as a Bearer token.

The Dockerfile bundles the AWS Lambda Web Adapter and a few AWS_LWA_* environment variables. These are inert outside of AWS Lambda and can be ignored (or removed) for a plain container/host deployment.

Running without Docker

uv syncuv run uvicorn src.main:app --host 0.0.0.0 --port 8080

Development

Requires uv and Python 3.14.

uv sync                 # install dependenciesuv run pytest           # run the testsuv run ruff check .     # lintuv run ruff format .    # format

License

MIT