Whether you care about air quality in a city, emissions from industry, or how companies stack up against climate expectations, Jana brings authoritative data into the tools you already use. With AI assistants—like the ones in ChatGPT, Cursor, Claude, or other modern workflows—you can ask questions in plain language and get answers grounded in real measurements and inventories, not guesswork.
Instead of wrangling multiple data sets, billions of records and complex APIs, you can explore air quality trends, greenhouse gas emissions, and facility-level signals through a single, conversational interface. AI helps you navigate complexity: you describe what you need, and Jana helps you find it—faster than traditional desk research, without sacrificing the seriousness of the underlying data.
From regulators, researchers, and investors to journalists and advocates, anyone who needs to see the picture clearly can use AI-powered access to environmental data that is global in scope and practical in detail. Jana is built for a world where decisions move quickly—and where trust in the numbers still matters most.
The Model Context Protocol (https://modelcontextprotocol.io) (MCP) is an open way for AI tools to call trusted capabilities in a predictable way; Jana’s MCP server exposes environmental data through that pattern so assistants can work with your platform safely and consistently. Under the hood, requests ride on **HTTP** semantics ([RFC 9110](https://www.rfc-editor.org/rfc/rfc9110)), structured data is exchanged as **JSON** ([RFC 8259](https://www.rfc-editor.org/rfc/rfc8259)), and production endpoints are served over **HTTPS** using **TLS** ([RFC 8446](https://www.rfc-editor.org/rfc/rfc8446))—the same RFC-backed stack enterprises already rely on for APIs and browsers. That means Jana’s AI integrations aren’t a one-off bridge: they align with widely recognized standards for how machines talk to machines (and how humans stay in the loop).
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