德國聯邦就業局 Jobsuche API：用 Python 搜尋超過 100 萬個德國職位（v6 端點）

The job board of Germany's Federal Employment Agency (Bundesagentur für Arbeit, arbeitsagentur.de/jobsuche) lists over 1 million open jobs: the largest job database in Germany, covering everything from nurses and electricians to software developers and apprenticeships. Its frontend talks to a JSON API that is open to everyone with a fixed public key.

Many tutorials and wrappers still use the old /pc/v4/jobs search endpoint, which now returns HTTP 403. Here's what works today (checked October 2026).

Search: /pc/v6/jobs

import requests

API = "https://rest.arbeitsagentur.de/jobboerse/jobsuche-service/pc"
HEADERS = {"X-API-Key": "jobboerse-jobsuche", "Accept": "application/json"}

r = requests.get(f"{API}/v6/jobs", headers=HEADERS, params={
    "was": "Softwareentwickler",   # what: job title or keyword
    "wo": "Berlin",                # where: city or postal code
    "umkreis": 25,                 # radius in km
    "size": 100, "page": 1,
})
data = r.json()
print(data["maxErgebnisse"], "matching jobs")
for job in data["ergebnisliste"]:
    print(job["stellenangebotsTitel"], "|", job.get("firma"), "|", job["stellenlokationen"][0]["adresse"].get("ort"))

Each result has the title, employer (firma), workplace address with coordinates, working-time flags, contract type (vertragsdauer), home office flag (homeofficemoeglich), publication date and the reference number (referenznummer).

Parameters that work

Two gotchas:

• 10,000 results max per query. page * size above 10,000 returns HTTP 400. Split big searches by location or date.
• There's no home office search parameter in v6. Filter on homeofficemoeglich == True yourself.

The response also contains facetten (facet counts per occupation, city, employer, working time…), which is handy for labor-market statistics without downloading jobs.

Salaries

About a quarter of listings state pay:

for job in data["ergebnisliste"]:
    if "gehaltsspanneVon" in job:          # range
        print(job["gehaltsspanneVon"], "-", job["gehaltsspanneBis"], job["verguetungsangabe"])
    elif "festgehalt" in job:              # fixed amount
        print(job["festgehalt"], job["verguetungsangabe"])

verguetungsangabe is the unit: JAHRESGEHALT (yearly), STUNDENLOHN (hourly) or KEINE_ANGABEN (none).

Details: still /pc/v4/jobdetails, base64-encoded

The full description is on a separate endpoint. Unlike search, it's still v4, and it wants the reference number base64-encoded:

import base64

ref = data["ergebnisliste"][0]["referenznummer"]
enc = base64.b64encode(ref.encode()).decode()
detail = requests.get(f"{API}/v4/jobdetails/{enc}", headers=HEADERS).json()
print(detail["stellenangebotsBeschreibung"][:500])
print(detail.get("istArbeitnehmerUeberlassung"), detail.get("allianzpartnerName"))

The details add the description, the temp-agency and private-recruiter flags, and allianzpartnerName/allianzpartnerUrl. Careful: the "Allianzpartner" is whoever delivered the posting, which is often a partner job board (jobvector, yourfirm…) and not the employer, so don't treat its URL as the company website unless the names match.

The public job page is https://www.arbeitsagentur.de/jobsuche/jobdetail/{referenznummer}.

Skip the plumbing

If you'd rather not handle pagination, the 10k cap, detail requests, salary normalization and English field names yourself, I packaged all of this as an Apify actor: Arbeitsagentur Jobs Scraper. It returns flat JSON (title, companyName, city, salaryMin, salaryMax, salaryInterval, remote, isTempAgency…), adds filters like remoteOnly, minSalaryYearly and excludeTempAgencies, and has a monitoring mode for daily feeds. It costs $2 per 1,000 jobs.

For AI agents

It's also callable as an MCP tool, for example from Claude or Cursor:

https://mcp.apify.com?tools=gleanery_actors/arbeitsagentur-jobs-scraper

Ask "find part-time nursing jobs in Hamburg posted this week, direct employers only" and the agent fills in the input. More job and B2B data tools for agents: github.com/gleanery-works/job-and-supplier-data-mcp.