Jobgent

An open-source AI job search engine you run yourself. Jobgent finds jobs, tells you which are worth your time and why, writes a tailored one-page CV and cover letter for each, and tracks every application. All of it from a web app, a CLI, or any AI agent over MCP.

It starts where its author needed it: internships for international students in the Netherlands, in English. The engine is general (search keywords, cities and dates are settings in your own profile), and the job sources are a list you can extend.

The model judges, code decides. The AI reads postings and drafts documents. Plain code decides the verdict, the coverage, what counts as evidence, and whether a document is safe to send. You submit every application yourself.

Try it in two minutes (no API key)

git clone https://github.com/Oxde/jobgent && cd jobgent
uv sync && uv run playwright install chromium
(cd frontend && npm ci --ignore-scripts && npm run build)
uv run jobgent demo                                  # a made-up student with 10 jobs
JOBGENT_HOME=~/.jobgent-demo uv run jobgent web       # http://127.0.0.1:8781

The demo is entirely fictional (Sam Jansen, generic companies) and never touches your real data in ~/.jobgent.

Related MCP server: career-agent-mcp

What it does

How it works

flowchart LR
    subgraph Sources
        ATS[Company ATS feeds]
        LI[LinkedIn public search]
        M[Link or pasted text]
    end
    Sources --> I[Ingest and dedupe] --> C[Classify: internship? English?]
    C --> G{Gates<br/>open, language, location,<br/>work rights, red flags, injection}
    G -- fail --> S[Skip, with the reason]
    G -- pass --> R[Model: extract requirements<br/>and point at evidence]
    R --> V[Code: coverage and verdict<br/>apply / consider / skip]
    V --> P[Model: tailor CV, write letter,<br/>review]
    P --> F[Code: banned phrases, fact guard,<br/>one-page PDF, ATS read-back]
    F --> T[Pack ready: you send it<br/>and track it]

Every model output is a typed schema (pydantic), so a model can only fill in fields; it cannot change the rules. Posting text is sanitized and fenced before any prompt sees it, so a posting that says "ignore your instructions" gets flagged instead of obeyed.

Use it from your AI agent

Jobgent is MCP-first: every feature is a tool, so Claude Code, Claude Desktop, Cursor or ChatGPT can drive the whole search by conversation.

claude mcp add jobgent -- uv --directory /ABSOLUTE/PATH/jobgent run jobgent mcp
uv run jobgent mcp --http        # port 8790, for ChatGPT connectors and other remote clients

Then just talk: "Find AI internships in Amsterdam starting February", "Is job 42 worth applying to?", "Make the pack for 42 in a direct tone", "Make my second bullet shorter", "What should I learn next?". The web app updates live while the agent edits.

No API key? Let your agent do the AI part. With evaluate_prompt / evaluate_submit and pack_prompt / pack_submit, Jobgent hands the agent the profile, the posting, the rules and the output format; the agent writes; Jobgent still runs every check (gates, verdict, fact guard, one-page PDF, ATS read-back) before anything is saved. Your Claude or ChatGPT subscription does the writing, and Jobgent stays the referee.

Set up for real

cp .env.example .env     # fill in what you have
uv run jobgent init
uv run jobgent web

With no AI key at all, search, tracking and the editor still work, and an MCP agent can do the AI steps (see above).

Your profile (~/.jobgent/profile/profile.yaml) is the single source of truth. Edit it on the Me page: the CV is a live A4 page you edit in place, next to a chat that edits it for you. Nothing personal is stored in this repository.

uv run jobgent init
uv run jobgent profile verify
uv run jobgent search "AI intern" --location Amsterdam
uv run jobgent fetch            # all sources → classify → score
uv run jobgent jobs --min-score 60
uv run jobgent pack 42
uv run jobgent status 42 applied
uv run jobgent stats
uv run jobgent agent            # one run of the daily job agent; --schedule 08:00 prints a launchd job
uv run jobgent companies        # check every board in data/companies.yaml
uv run jobgent eval             # run the golden evals against the live model
uv run jobgent web | mcp | demo

Quality

• 250 tests that need no network and no API keys (uv run pytest -q), and mypy --strict on the whole package.

• Golden evals: 10 hand-written postings in evals/golden/ cover a strong fit, Dutch required, Dutch as a plus, the wrong city, an unpaid role, an agency fee, a prompt injection, a critical gap, a weak fit and a closed posting. Tests replay recorded model output; jobgent eval runs them against the live model.

• Security: link fetching blocks private addresses and re-checks every redirect (SSRF), secrets are never logged or returned by the API, and posting text is treated as data, never as instructions. See SECURITY.md.

Screenshots

Stack

Python 3.12 (uv), FastAPI, SQLAlchemy + SQLite, pydantic, FastMCP, Typer, Playwright for PDFs. React 19, Vite, Tailwind 4, dnd-kit. Claude (Anthropic API or KIE) as the model.

Agent skills

.agents/skills/ holds skills that coding agents load when working in this repo. jobgent-cv-writing (ours) overrides the rest: facts only from the profile, never an estimated number, gaps stated honestly. The others come from ResumeSkills by Param Choudhary (MIT), anthropics/skills (frontend-design) and ui-ux-pro-max (MIT). skills-lock.json pins them.

Roadmap

• Indeed and a generic careers-page reader for companies without a public ATS feed.

• Import a profile from a CV PDF.

• More countries and languages.

• A hosted version for students who don't want to run it locally.

Ideas, bug reports and job boards are welcome: see CONTRIBUTING.md. Adding a company is a one-line change.

Credits

Ideas for the evaluation and the pack were studied from career-ops, ai-job-search and Dossier. The design history is in docs/design/.

License

MIT © Oxde