aijobsboom-x402
x402-gated data API (Cloudflare Worker) plus an MCP server wrapper serving aggregate weekly stats from the aijobsboom.com skilled-trades job board — trade counts, perk flags, scrub-rule counts. $0.01/$0.10 USDC per call, no raw job listings.
README
aijobsboom-x402
x402-gated data API for the aijobsboom.com skilled-trades job board, plus an MCP server wrapper that pays for calls on an agent's behalf.
Live API: https://aijobsboom-x402.sonofgus.workers.dev
What this is
Rollup statistics from the aijobsboom pipeline — counts, not listings. Every pipeline run appends one row: total rows pulled, rows removed per scrub rule, per-trade counts (electrician, HVAC, lineman, welder, mechanic, CDL), and perk-flag counts (fair-chance, will-train, per diem, day-1 benefits, sign-on bonus, travel paid, employer-posted six-figure, HOT count, North Dakota, Montana). No job titles, employer names, posting URLs, or descriptions are served anywhere in this dataset — see methodology.md for why.
Endpoints
| Endpoint | Price | Network |
|---|---|---|
GET /methodology |
free | — |
GET /snapshot |
$0.01 USDC | Base |
GET /series?weeks=N |
$0.10 USDC | Base |
Payment is enforced via x402 — no accounts, API keys, or subscriptions required.
MCP server
mcp-server.js wraps the API as two MCP tools, get_snapshot and
get_series. It holds its own Base wallet (funded with USDC) and pays for
each gated call itself via x402-fetch, so the calling agent just invokes a
tool and gets JSON back.
npm install
AIJOBSBOOM_API_BASE=https://aijobsboom-x402.sonofgus.workers.dev \
X402_CLIENT_PRIVATE_KEY=0x... \
npm run mcp
X402_CLIENT_PRIVATE_KEY is the 0x-prefixed private key of a Base wallet
funded with USDC — never commit this.
Worker deployment
npm install
wrangler secret put X402_WALLET # the Base address that receives USDC
wrangler secret put FACILITATOR_URL # optional, overrides the default facilitator
npm run deploy
Data updates: after each pipeline.py run in the parent repo, copy the fresh
archive/stats.csv over data/stats.csv, run npm run teaser to refresh
teaser.html, then redeploy. The CSV is bundled into the Worker at build
time — there's no runtime data fetch.
Docs
Full column dictionary, scrub-rule writeup, and ToS constraints: methodology.md.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.