Optifeed Radar MCP server

Optifeed Radar

Open-source AI visibility checker. Now on npm - run it with npx optifeed-radar.

Is your brand recommended when buyers ask AI? Optifeed Radar checks whether the models behind ChatGPT, Perplexity, Gemini and Claude actually recommend you, and tells you where you stand against competitors. It runs locally, uses your own API keys, and has no Optifeed-hosted backend.

It is built for two kinds of AI agents at once: it measures how AI agents see and recommend you, and it can be run by your own AI agents (CLI, JSON, and an MCP server). People also call this AI visibility, generative engine optimization (GEO), answer engine optimization (AEO), or AI-SEO.

60-second setup

No install needed - npx fetches and runs it. The zero-key audit runs end to end with no API keys and no AI calls:

npx optifeed-radar audit yourbrand.com

It checks AI-crawler access (robots.txt), llms.txt, schema.org structured data, meta basics, and your sitemap, then prints a 0-100 AI-readiness score.

The check pipeline runs once you set at least one engine API key. Put it in a .env file in the directory you run from, or export it:

echo "OPENAI_API_KEY=sk-..." > .env      # any one engine key gets you started
npx optifeed-radar check yourbrand.com

The CLI loads .env from the directory you run it in, so there is no shell setup step. Exporting the keys works too (export OPENAIAPIKEY=...), and an exported key always wins over the same key in .env. config shows which keys were found and which file they came from, never the values.

It discovers your brand, generates a buyer-prompt pack, asks the engines, and scores recommendation, position, and share of voice into one AI Visibility Score. The score reads only the unbranded buyer questions (did the AI surface you unprompted); questions that name your brand are reported separately as reputation. All four engines are verified live against their production APIs (2026-07-20).

Working from a clone instead? Run npx tsx src/cli/index.ts so flags reach the CLI unchanged, or use the npm run dev script with -- before the arguments (npm run dev -- check yourbrand.com --report out.html).

Install the Agent Skill

Radar also ships as an open Agent Skill for Codex, Claude Code, Cursor, and other compatible AI agents. Install it directly from this repository:

npx skills add optifeed/optifeed-radar --skill optifeed-radar

Add -g to make it available across your projects. Then ask, for example:

Use $optifeed-radar to run the free AI-readiness audit on yourbrand.com,

explain the three highest-impact findings, and do not start a paid check.

The MCP server supplies executable tools. The Agent Skill supplies the working method around them: start with the zero-key audit, confirm scope and cost before paid engine calls, use a cap, and report sampling limits with the result. The skill can also drive the CLI when MCP is not configured.

Install the Claude Code plugin

Shortened. The full README is on GitHub.