Why We Built ApiCrate

Every project has that moment. You need to hash a password, parse a user agent, validate a postal code, or geolocate an IP. You've done it before. You'll do it again. Each time you pull in a library, write a wrapper, handle edge cases, and hope the dependency doesn't break on the next update.

We built ApiCrate to make that moment disappear.

The Problem¶

Developer utility APIs are everywhere, but they're fragmented. You get user-agent parsing from one provider, hashing from a library you vendor, geolocation from a freemium service with opaque rate limits, and country data from a static JSON file you found on GitHub three years ago.

Each one has its own auth model, response format, error conventions, and quota system. Your code ends up with five different HTTP clients, five different error handlers, and five different API key management strategies.

ApiCrate consolidates all of this into one platform — one API key, one consistent JSON format, one quota system, one set of docs.

What's Inside¶

ApiCrate provides a growing set of utility endpoints that developers reach for constantly:

Every endpoint returns structured, predictable JSON. Every endpoint uses the same authentication. Every endpoint counts against the same quota.

AI-First by Design¶

Most APIs were built for human developers writing code. ApiCrate is built for a world where AI agents are the primary consumers.

What does that mean in practice?

• Structured, self-describing responses — every field has a consistent name and type across endpoints. An LLM can parse the response without guessing.
• Predictable error formats — agents can programmatically handle errors without parsing human-readable messages.
• Flat, filterable payloads — the ?fields= parameter lets agents request only what they need, reducing token usage and improving context efficiency.
• No browser-dependent flows — no OAuth redirects, no cookie-based sessions. Just an API key in a header.

When an AI agent needs to check if an email is from a disposable domain, validate a postal code, or hash a password, it shouldn't need to search npm, read docs, install packages, and handle dependencies. It should call one API.

First-Class MCP Server¶

This is where it gets interesting. ApiCrate ships a Model Context Protocol (MCP) server that exposes every API endpoint as a tool that AI agents can call directly.

{
  "tool": "apicrate-parse-user-agent",
  "input": {
    "ua": "Mozilla/5.0 (iPhone; CPU iPhone OS 17_0 like Mac OS X)..."
  }
}

The MCP server means Claude, GPT, and other LLM-powered agents can use ApiCrate without any glue code. No SDK installation. No wrapper functions. The agent discovers the tools, understands their schemas, and calls them.

Every utility API becomes a capability that any AI agent can use out of the box.

We designed the MCP tools to be:

• Self-documenting — tool descriptions explain what they do, what they return, and when to use them
• Composable — an agent can chain geolocate-ip → lookup-country → find-nearby-postal-codes in a single conversation
• Bulk-aware — tools like parse-user-agents-bulk and check-email-risk-bulk handle batch operations efficiently

One Key, Everything Works¶

Sign up, get an API key, and every endpoint works immediately. No per-service billing. No separate dashboards. Your quota is shared across all endpoints, and you can see exactly how you're using it from a single dashboard.

For AI agents, this is critical. An agent doesn't want to manage multiple API keys or figure out which service handles which task. One key unlocks the entire toolkit.

What's Next¶

We're adding new endpoints regularly — carbrands API, QR code generation, and more. Every new endpoint automatically becomes available as an MCP tool.

If you're building AI agents, internal tools, or just want to stop rebuilding the same utility APIs, sign up and grab your API key. It's free to start.