HiringCafe MCP Server

A minimal, no-auth remote MCP server built with Next.js and the Vercel MCP SDK (mcp-handler). It lets an MCP client (like ChatGPT) search HiringCafe using its public HTML pages — no internal API, no database, no browser automation.

How it works

HiringCafe is a Next.js app that server-renders a structured __NEXT_DATA__ JSON island into every public HTML page. This server fetches those public pages over plain HTTP and parses that island with cheerio, which is far more robust than scraping CSS class names. Results are cached in memory by job URL for the lifetime of a warm serverless instance.

• No auth

• No database

• No frontend app (a small status page is served at /)

• No browser automation / Playwright

• No background crawling or pagination (first page only)

• All page content is treated as untrusted text

Related MCP server: jobfinder-mcp

Endpoints

MCP tools

search_jobs

Search listings by role and/or location.

// input
{ "query": "software engineer", "location": "Seattle, WA" }
// -> fetches https://hiring.cafe/jobs/software-engineer-seattle-wa

Returns { jobs: [{ id, title, company?, location?, salary?, workplace_type?, employment_type?, summary?, skills?, url }] }.

get_job

Fetch and parse a single /job/... detail page.

{ "url": "https://hiring.cafe/job/<job-slug>" }

Returns { id, title, company?, location?, salary?, workplace_type?, employment_type?, requirements_summary?, tools?, description?, url }.

search (ChatGPT-compatible)

Free-text search that returns compact, citation-friendly results.

{ "query": "SRE jobs in Bellevue" }
// -> { results: [{ id, title, url }] }

fetch (ChatGPT-compatible)

Return full text + metadata for a job by the id from search/search_jobs.

{ "id": "<id>" }
// -> { id, title, text, url, metadata: { source: "hiring.cafe", company?, location? } }

Ids are base64url-encoded job URLs, so fetch works even on a cold instance where the in-memory cache is empty.

URL slugging

Route building lives in lib/slug.ts so it can be adjusted if HiringCafe changes its URL patterns:

"Seattle, WA"       -> "seattle-wa"
"Software Engineer" -> "software-engineer"

query + location -> /jobs/{query-slug}-{location-slug}
location only    -> /jobs/{location-slug}
query only       -> /jobs/{query-slug}

Local development

pnpm install
pnpm dev

• App: http://localhost:3000

• Health: http://localhost:3000/api/healthz

• MCP: http://localhost:3000/api/mcp

Deploy to Vercel

Push the repo and import it into Vercel, or:

vercel deploy

No environment variables are required. Your MCP endpoint will be:

https://<your-deployment>.vercel.app/api/mcp

Connect from ChatGPT

1. In ChatGPT, open Settings → Connectors (or a custom GPT's Actions/MCP).

2. Add a new remote MCP server with the URL: https://<your-deployment>.vercel.app/api/mcp

3. No authentication is needed.

4. ChatGPT will discover the search_jobs, get_job, search, and fetch tools.

Example prompts

• "Search HiringCafe for software engineer jobs in Seattle"

• "Find SRE jobs in Bellevue"

• "Fetch details for this job: https://hiring.cafe/job/"

Project structure

app/
  api/
    mcp/route.ts      # MCP server + tool definitions
    healthz/route.ts  # liveness probe
  page.tsx            # status page
lib/
  hiringCafe.ts       # fetch + parse public HiringCafe HTML
  normalize.ts        # id/text/skill normalization helpers
  slug.ts             # slug + route builders
  cache.ts            # in-memory job cache
  types.ts            # shared types

Safety

• All outbound fetches have a hard timeout.

• Results are limited to the first listing page (no pagination crawling).

• No login, no applying to jobs, no writes to HiringCafe.

• Page content is treated as untrusted text.