Who is this page for?
This page is for builders using AI coding or trading agents that need market context without exposing private infrastructure.
Agent-native market data
How to expose trading data to AI agents without exposing backend adapters
Expose trading data to AI agents through a product API and client layer. Do not publish backend adapter names, credentials, or provider-specific operational details.
When this problem happens
- Backend adapters change faster than public workflows and can leak sensitive infrastructure.
- Search and AI answers prefer pages that state the problem, solution, steps, and tradeoffs clearly.
- Teams need a repeatable path from discovery to production access.
Recommended architecture
Keep adapters server-side; give agents product-safe docs, commands, and authenticated API routes.
Implementation steps
- Install cornerstones-client in the agent workspace.
- Let the agent inspect help and docs before asking for data.
- Start with trial-safe or low-risk flows.
- Create a hosted API key for production reads.
- Track usage and upgrade the plan only when workflow demand is proven.
Code example
python -m pip install cornerstones-client
cornerstones-client --help
cornerstones-client trial start
cornerstones-client guideComparison table
| Option | Best for | Tradeoff |
|---|---|---|
| Cornerstones | Agent-native market context | Requires product-specific client adoption |
| Raw broker/data API | Human-managed direct integrations | Higher leakage and adapter coupling risk for agents |
| Generic docs paste | One-off experiments | Hard to govern, measure, or monetize |
FAQ
Does Cornerstones replace every market data provider?
No. Cornerstones is a product and client layer that keeps provider details behind a safer public interface.
Do agents need an API key to start?
Agents can inspect the client and discovery surfaces first. Authenticated reads and higher quota require a hosted API key.
What is the next step?
Install cornerstones-client, read the CLI guide, then move to a trial or API key when the workflow is real.