agent-data – Real-Time Structured Data for AI Agents

TL;DR

TL;DR: agent-data is a CLI that replaces slow, token-heavy browser automation with a fast API-first approach to fetching real-time structured data for AI agents.

Source and Accuracy Notes

⚠️ This section is MANDATORY. All links must be verified from actual source, not guessed.

• Project page: agent-data.dev ← MUST visit and verify
• Docs: docs.agent-data.dev ← MUST read
• HN launch thread: news.ycombinator.com/item?id=48052476 ← verified via HN Algolia API
• License: No source repository found — this is a hosted SaaS product

What Is agent-data?

Most websites are designed for humans, not agents. When an AI agent needs real-world data — flight options, restaurant availability, social media posts — developers typically reach for browser automation. That approach has three problems:

1. Every step requires a screenshot before the agent can decide what to do next.
2. Each screenshot and DOM dump burns thousands of tokens.
3. One layout change, modal, captcha, or blocked request breaks the whole run.

agent-data solves this by exposing a CLI that wraps real-time web data behind a clean API. Instead of “open Chrome, navigate to Google Flights, read the page,” an agent calls:

agent-data search "flights SFO to JFK next Saturday"

And gets back structured JSON — no screenshots, no DOM parsing, no token waste.

The tool integrates with OpenClaw, Claude Code, and Hermes MCP at launch, with an MCP server for broader compatibility.

Installation and Setup

Prerequisites

• Node.js 18 or later (for the MCP server)
• An agent-data account (free tier: 100 calls/month)

Install the CLI

npx -y agent-data init

Or globally via npm:

npm install -g agent-data

After initialization, the CLI authenticates automatically and you’re ready to query.

MCP Server Setup

For Claude Code and other MCP-compatible agents:

agent-data mcp start

This starts a local MCP server the agent connects to for structured data lookups.

Available Data Operations

From the docs, agent-data exposes several operation types:

• Flight information — real-time flight options, pricing, and schedules
• Restaurant availability — current open slots at restaurants
• Social monitoring — structured social media data by subreddit or topic
• Job postings — aggregated listings filtered by criteria
• Sportsbook odds — live odds data
• AI blog aggregation — content discovery across AI/ML blogs

Each operation returns typed JSON rather than raw HTML, so the agent gets immediately actionable data.

Pricing

agent-data uses a tiered pricing model:

| Plan | Price | Calls/month | |---|---|---| | Free | $0 | 100 | | Pay-as-you-go | $0.008/call | Unlimited | | Starter | $30/mo | 4,000 | | Growth | $100/mo | 15,000 | | Scale | $200/mo | 40,000 |

Failed requests (4xx, 5xx) and rate-limited retries are never billed. A spend cap can be set in the dashboard to prevent overages.

How It Compares to Browser Automation

The agent-data landing page benchmarks three approaches: browser automation, search/scraping, and agent-data’s API-first method.

Browser automation typically takes 30–120 seconds and burns 50,000–100,000 tokens per task. agent-data returns structured data in under 1 second with a fraction of the token cost.

Search and scraping return link lists and snippets — not the actual data an agent needs to act. agent-data returns structured, machine-readable responses directly.

Practical Evaluation Checklist

• CLI installs and authenticates without a credit card on free tier
• MCP server starts cleanly and is reachable by the agent
• At least one operation (e.g., flight search) returns structured JSON
• Spend cap can be set from the dashboard
• Docs are readable and cover all operations listed

Security Notes

• Authentication is tied to your account — keep CLI credentials local
• The MCP server runs locally; no remote code execution risk from the server itself
• Rate limiting applies per-plan; pay-as-you-go has no hard limit but costs accumulate
• No data retention policy was found in the docs — if your agents query sensitive data, clarify retention with the vendor before production use

FAQ

Q: Is there a GitHub repository for agent-data? A: No — agent-data is a hosted SaaS product. The CLI is distributed via npm/npx, not as open-source code. There is no public source repository.

Q: Does it work with agents other than OpenClaw, Claude Code, and Hermes? A: Yes — the MCP server provides a generic interface any MCP-compatible agent can use, not just the three named explicitly.

Q: How is the free tier different from the paid tiers? A: The free tier gives 100 calls per month with no credit card required. Paid tiers increase call volume and add email support.

Q: Can I self-host agent-data? A: No. agent-data is a hosted service. There is no self-hosted option at this time.

Q: What happens if I exceed my plan’s call limit? A: Your agent keeps running. Overage calls are billed at the pay-as-you-go rate of $0.008 per call.

Conclusion

agent-data fills a real gap in the AI agent ecosystem: structured, real-time web data without the token overhead and fragility of browser automation. The free tier is generous enough to evaluate thoroughly, and the MCP server makes it accessible to any agent that supports the MCP protocol. If your agents currently rely on Playwright or similar browser automation for data retrieval, agent-data is worth comparing directly.

For a deeper benchmark comparing browser automation, scraping, and API-first approaches, see the writeup on the agent-data site.