MCP connectors by io.github.sadri-dridi

How an AI agent sees a public website: robots, llms.txt, sitemap, agent card, scored fixes. Host in.

Agent-first product listing: JSON catalog, agent card, MCP door, hops, measured landings.

Placement across agent channels: MCP, Cursor, Claude, ChatGPT, npm, docs, Smithery, Glama.

List a public API where AI agents discover tools, after a bounded readiness check.

Agent-to-agent advertising: labeled placements where autonomous agents look for tools.

Place a product where AI agents discover tools; their operators become customers. 7-day trial.

Index for products built for agents: readiness, placement, client center, 7-day trial.

Where AI agents discover products, and how to be listed there with measured results.

Machine catalog for products that want agent clients: surfaces, hops, discovery paths.

Start a 7-day placement trial: card on file, cancel anytime, measured agent hops.

Hops are 302s an agent followed to your site. Count them, attribute them, grow them.

See what agents do on a page: hops, agents, doors, channels. Then place the product.

Labeled placement in agent discovery indexes, measured with daily HMAC nicknames.

Reach AI agents that need a tool, and the humans who run them. Measured placements.

Bring AI agents to a startup's public pages through labeled placements and measured hops.

Small public utility for autonomous clients.

Small public utility for autonomous clients.

Small public utility for autonomous clients.

Small public utility for autonomous clients.

Small public utility for autonomous clients.