One Week Later: What I Learned from Launching an AI Agent API and a Curated MCP Registry

One Week Later: What I Learned from Launching an AI Agent API and a Curated MCP Registry

posted Originally published at dev.to 2 min read

Let's be honest. I launched AgentShare – a price infrastructure API for AI agents – a week ago. The post got some traction. People liked the idea. But I quickly learned that shipping a REST API is only half the battle.

1. The MCP shift was faster than I expected

Developers don't want to read documentation. They want to plug and play. Within days of adding an MCP server (mcp-remote https://agentshare.dev/mcp), I saw people using it directly inside Cursor, Claude Desktop, and even playing with it in automation scripts. The friction almost disappeared.

If you're building for AI agents, MCP is not optional anymore. It's the USB-C of this ecosystem (and Anthropic's Model Context Protocol is quickly becoming the standard).

2. I built a curated registry

The next realization? Finding quality, actually-working MCP servers is a scavenger hunt. Most directories are noisy, unverified, and full of dead links.

So over the last few days, I built a small curated MCP registry at agentshare.dev/registry.

  • Every listing is editor-reviewed before going live.
  • No API key required to browse – simple, machine-readable JSON endpoints (GET /api/v1/registry/entries).
  • It's a closed, high-signal list for data, operations, and commerce-adjacent tools.

Right now it features my own AgentShare MCP, a few official reference servers, and placeholders for common patterns (analytics pipelines, web scraping, Slack ops). I'd love to see what the community submits next.

3. Reliability really is the hidden currency

I've been running my agent agentshare_claw on Moltbook – a social network where AI agents talk to each other.

Here's what I learned:

  • Agents ignore ads, banners, and affiliate links.
  • They care about structured JSON, freshness_status, and data_age_seconds.
  • They also reward uptime and predictable error responses.

We're currently tracking 168 Karma on Moltbook. No hype. Just utility. "Reliability as a currency" is not a slogan – it's a measurable economic signal. (Just ask who fills the orders when price data goes stale.)

4. Feedback I'd love from you

I'm not here to sell. I'm here to learn.

  • Is the JSON response shape easy to work with in your agent framework?
  • How old is "too old" for a price in your use case?
  • What hardware or component categories are you missing?

The goal is to build a B2A platform (Business to Agent) that honestly serves the agent economy. Not AI wrappers. Actual infrastructure.

Try it:

Learn. Build. Iterate.

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