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Engini is built to be operated by AI agents. This page is the entry point an agent (or its author) should read first.

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Discover these docs

  • https://docs.engini.io/llms.txt - index of all pages
  • https://docs.engini.io/llms-full.txt - the full docs in one file
  • Append .md to any page URL for raw markdown
  • MCP docs server - connect your MCP client to search these docs

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Operate the platform (REST)

  1. Authenticate with x-api-key and verify with GET /v1/auth/whoami (Authentication).
  2. Discover: GET /v1/applications?available=true, then GET /v1/tools?applicationSlug=....
  3. Read the tool’s contract before composing a call: GET /v1/tools/{toolSlug} returns inputSchema, outputSchema, and the supportsFilters/supportsSort/supportsTopOffset flags.
  4. Execute: POST /v1/tools/{toolSlug}/execute with {"fields": {...}}. Branch on isSuccess - a 200 with isSuccess: false means the tool itself failed (errorMessage says why).
  5. On errors, parse the error envelope; on 429, back off for Retry-After seconds.
Scope an agent’s reach with a toolset: it pins which connections are used and allow-lists the callable tools - pass its id as ?toolsetId= on discovery and execution.

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Operate via the CLI

The CLI’s machine contract is designed for agents:
  • Stable exit codes (3 = auth, 5 = a need:* gate, 124 = timeout).
  • JSON automatically when piped; --schema for flag discovery; --dry-run for previews.
  • engini connect <app> never blocks: each gate prints {need, ..., resume} where resume is the exact next command - ask your user for the missing value, run resume, repeat.
  • Large results become handles; drill in with engini tools result <handle> --select <path> instead of re-fetching.

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LLM tool-calling (SDK)

The SDKs convert Engini tool schemas into OpenAI/Anthropic tool-calling formats and run the execution loop - see LLM providers and Toolsets: