brandfetch MCP

by brandfetch

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About

MCP Server to connect to Brandfetch services

Details

Author
brandfetch
Categories
Design, API

Setup

Install brandfetch MCP in your MCP client (Claude Desktop, Cursor, Windsurf, and others).

Repository: https://github.com/brandfetch/brandfetch-mcp-server

Follow the installation instructions in the repository README, then restart your MCP client.

The officialModel Context Protocolserver forBrandfetch. It gives AI assistants access to brand search, company data, logos and design assets, and LLM-ready brand context from the Brandfetch API.

Full documentation:https://docs.brandfetch.com/mcp/overview

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

Authentication uses a Brandfetch MCP token (abf1.bearer token). Generate one from theKeys and MCPpage in theBrandfetch dashboard, or connect via OAuth from a client that supports it.

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

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" } } } }

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

This is an HTTP (streamable-http) MCP server built withFastMCP. 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 onhttp://localhost:8080/mcp. Point your MCP client at that URL and send your Brandfetch credentials as aBearertoken.

TheDockerfilebundles theAWS Lambda Web Adapterand a fewAWS_LWA_*environment variables. These are inert outside of AWS Lambda and can be ignored (or removed) for a plain container/host deployment.

uv sync uv run uvicorn src.main:app --host 0.0.0.0 --port 8080
uv sync # install dependencies uv run pytest # run the tests uv run ruff check . # lint uv run ruff format . # format

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