Developer Portal

Introduction

Admetrics Developer Portal helps developers connect AI agents, Chat Apps, backend systems, and customer data platforms to validated Admetrics data through the Admetrics Query Language (AQL) via MCP and the REST API.

Use MCP when an agent, coding tool, or Chat App should call the Admetrics analytics tools directly. Use the REST API when a backend service, workflow, or integration needs explicit HTTP contracts and direct structured-query execution. Teams can use both to enrich their own BI layer, notebooks, automation jobs, semantic stores, and internal data products with catalog-validated marketing analytics.

What AQL Does

AQL (Admetrics Query Language) is the translation layer between developer-friendly analytics requests and the Admetrics data warehouse model. A caller sends natural language through MCP or a structured analytics query through the REST API. AQL turns that into warehouse-ready queries with the right clients, metrics, dimensions, grouping, date filters, attribution parameters, sorting, limits, and result format.

That means the integration code does not need to know every warehouse table, join, attribution rule, or output serializer. Developers work with catalog IDs and validated query JSON; AQL handles the warehouse query shape and returns results as records, rows, columnar JSON, text/CSV, spreadsheets, dataframe-oriented payloads, or Arrow.

Choose Your Integration

  • MCP: best for ChatGPT, Claude Code, Codex, OpenCode, and generic tool-calling clients.
  • REST API: best for backend jobs, application services, notebooks, data-platform ingestion, and controlled production workflows.
  • Catalog Explorer: use this before running production queries so metric, dimension, client, and sort IDs are exact.
  • Query Builder: build structured analytics queries from catalog selections, default to Arrow output, and inspect table previews.
  • API Access: create, list, report on, and revoke managed API keys for server-side integrations and local development.

Build On Your Data Platform

Admetrics can be the analytics access layer that augments an existing warehouse, dashboard stack, or internal developer platform. Use catalog IDs as stable contracts, fetch Arrow or JSON results through REST, and let agent workflows discover and explain the same metrics through MCP. This keeps teams from rebuilding metric semantics in every notebook, job, or app while still letting them own the surrounding data platform.

Current Scope

Public docs are available without sign-in. Live catalog, Query Builder, and token creation are authenticated. They use user-specific Admetrics permissions.

Production Rule

Do not commit JWTs or OAuth tokens. Store tokens in environment variables, secret managers, or deployment secret stores.