HiringCafe MCP Server
Enables searching and fetching HiringCafe job listings through MCP, using public HTML pages without authentication or browser automation.
README
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
Endpoints
| Endpoint | Purpose |
|---|---|
/api/mcp |
MCP server (Streamable HTTP) |
/api/healthz |
Liveness probe (returns 200) |
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
fetchworks 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
- In ChatGPT, open Settings → Connectors (or a custom GPT's Actions/MCP).
- Add a new remote MCP server with the URL:
https://<your-deployment>.vercel.app/api/mcp - No authentication is needed.
- ChatGPT will discover the
search_jobs,get_job,search, andfetchtools.
Example prompts
- "Search HiringCafe for software engineer jobs in Seattle"
- "Find SRE jobs in Bellevue"
- "Fetch details for this job: https://hiring.cafe/job/<job-slug>"
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.
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