The fastest-growing class of AstroFabric callers is not backend services. It is AI assistants: Claude Code in a terminal, Cursor in an editor, custom agents inside our customers' products. They speak the Model Context Protocol, so the platform does too, natively.
{
"mcpServers": {
"astrofabric": {
"url": "https://www.astrofabric.ai/api/mcp",
"headers": { "Authorization": "Bearer ek_live_..." }
}
}
}That one entry gives the assistant the full tool catalog with input schemas: audits, visibility checks, deliverability scoring, search analytics. Ask "why did signups from organic dip?" and the model can pull Search Console data, audit the landing pages and answer with evidence, in one conversation.
Same key, same rules
The MCP surface authenticates with the same API keys as REST, honors the same scopes, bumps the same meters and hits the same budget ledger. There is no side door where an enthusiastic agent can spend outside the envelope; a budget stop reaches the model as a readable error it can explain back to you.
If you are building an assistant rather than using one, the same server works as a remote toolbox for any MCP-capable framework. Mint a key with narrow scopes and hand your agent exactly the capabilities you want it to have.
Every playbook on this blog ships as a runnable mission.
Open a free workspace and the playbook library is waiting - describe the outcome and the agents carry it end to end, with 1,000 trial credits on us.