Zaira Labs is live. We build trust signals for agents, starting with two products: an open standard for evaluating whether developer tools are ready for AI coding agents, and a guide that gives those agents verified, structured intelligence for tool decisions.
What is it?
The Zaira Standard defines what “ready for agents” means for developer tools. 71 criteria across 12 modules, drawn from 40+ academic papers and benchmarks among 85 cited sources, analysis of more than 10,800 MCP servers, and direct measurement of how agents actually interact with developer tools. Open methodology, versioned, free to read and argue with.
The Zaira Guide is structured decision data for developer tools: what to use when, what to avoid, what the alternatives are, and why. Over 900 tools across 60 categories and growing, nearly 4,000 pages of editorial content, every entry verified against public evidence. When we can’t verify a fact, we publish nothing instead of guessing. Available as web pages, a REST API, and an MCP server. Same data, three channels.
Why now
Agents are picking developer tools today, at scale. Every coding session, they choose databases, auth providers, and frameworks, and the stack they choose is often the difference between shipping and stalling.
The bad news: they’re bad at it. And it’s not their fault. Training data goes stale in months. Web searches land on 2022 Stack Overflow answers. Package names get hallucinated at a roughly 20% rate. At best, docs tell an agent how to use a tool, never which tool to use. Nobody has published structured data for the question agents actually ask: given these constraints, what should I use, and why?
So we built it!
Structured retrieval reduced agent hallucination by up to 91% in early benchmarks. The problem is fixable.
How the pieces fit
The Standard defines what agent-ready means. The Guide presents developer tools in an agent-ready way, with every tool scanned against the Zaira Base Standard and the score broken into sections, so a “63” tells you where the “63” comes from. Trust signals are our products, so the rules are strict: we don’t sell placement, vendor money never changes a score, the methodology is public, and the results are reproducible.
It’s already working. In our two-week soft launch, with zero promotion, the Guide served ~46,000 requests and AI answer engines have already started citing it: AI assistants fetch Guide pages hundreds of times a day on behalf of live users, over 500 daily fetches from ChatGPT, Claude, and Perplexity across 700+ unique pages. Within hours of our MCP server appearing on its first registry, verified agents from Anthropic’s and OpenAI’s platforms connected and started querying. Agents are finding the data useful before we even announced it existed.
Try it
The Guide is live now. No key, no signup, no waitlist.
https://zairalabs.ai/guide/api/v1/tools?category=relational-database&selfHostable=true&limit=100 That query returns every relational database in the Guide you can self-host, as structured JSON an agent can filter. Any single entry also serves as Markdown-KV via Accept: text/markdown. Your coding agent can do the same mid-session through the MCP server, or read the tool pages via HTML the way answer engines already do. You can check out the entire API spec on the developers page.
What’s next
This post is the first of three big drops. Next, we go deep on the Standard: what the overused buzzword “agent-ready” actually means and how the score works. Then, the Guide: how we build decision data agents can trust. After that, we start dropping the fun, functional stuff: best-practices guides, Claude Code skills, and real examples of it all in action.
We started Zaira Labs out of equal parts awe and frustration building with AI tools. It’s a fun time to be building in this space. The internet has a new kind of user. Software has a new kind of developer. We’re working to build the trust signals that set that new user, and the humans it supports, up for success.
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