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

Tool	Description
`brand_search`	Search for brands by name using Brandfetch's search index.
`get_brand`	Look up full brand data by domain, email, ticker, ISIN, or crypto symbol; renders the interactive brand card on MCP Apps hosts.
`get_brand_data`	The same brand data with no card — for logo walls, multi-brand work, and data that feeds generated content.
`enrich_transaction`	Identify a merchant brand from a credit-card or bank-statement string.
`get_brand_context`	Get LLM-ready brand context for a domain — voice, audience, positioning, style.
`build_logo_urls`	Construct Brandfetch Logo CDN URLs for one or more brands (no API call).
`send_feedback`	Report bugs, wrong or stale brand data, or missing capabilities to Brandfetch.

Interactive brand card (MCP Apps)

On hosts that support the MCP Apps extension (claude.ai, Claude Desktop, ...), 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, so a logo wall of six brands is six data calls rather than six cards; the model picks between the two by their descriptions. The widget source lives in ui/ and is served by the server as the ui://brandfetch/brand-card.html resource.

Quick start (hosted server)

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

Code

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

config.json

{
  "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):

config.json

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

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, 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.

429 "API quota exhausted" — your key has used all of its API credits. Check usage or upgrade in the Brandfetch dashboard.
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.

Terminal

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

bash

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

Development

Requires uv and Python 3.11.

bash

uv sync                 # install dependencies
uv run pytest           # run the tests
uv run ruff check .     # lint
uv run ruff format .    # format

License

MIT