job-search-mcp

Infrastructure for running a job search with Claude Code. Point it at a folder with your CV + a small config; it discovers roles, fetches each company's exact application fields, drafts non-trivial applications (positioning, not just autofill), and renders a navigable, offline dashboard with one-click copy for every field. Nothing is auto-submitted — you review and send.

Works two ways: as a set of Claude Code skills + an MCP server (talk to Claude), or as a CLI.

What it does

Design principle — human-in-the-loop. It prepares applications; you submit them. Fully-automated apply bots violate LinkedIn policy (permanent-ban risk) and are out of scope by design.

Related MCP server: Job Search MCP Server

Your data folder

You keep your inputs and outputs in one folder, separate from this repo. Point the tool at it with --data-dir or the JOBSEARCH_DATA env var.

my-jobsearch/
  profile.json          # from parse-cv, or copy examples/profile.example.json
  config.json           # optional; copy examples/config.example.json
  companies.json        # optional; a curated target list (Claude can research one)
  nontrivial_kits.json  # optional; pre-authored per-company kits
  output/jobs.json      # written by the tool
  applications/*.json   # written by the tool
  dashboard.html        # written by the tool

Setup

python3 -m venv .venv && source .venv/bin/activate   # Python 3.10+
pip install -r requirements.txt
export ANTHROPIC_API_KEY=…        # optional: LLM CV-parsing + auto-drafted non-trivial kits

Use it — CLI

D=~/my-jobsearch
python -m src.cli --data-dir $D parse-cv --cv ~/MyCV.pdf     # CV -> profile.json
python -m src.cli --data-dir $D scrape                       # -> output/jobs.json
python -m src.cli --data-dir $D apply --url "<job_url>"      # -> applications/<company>.json (+ non-trivial kit)
python -m src.cli --data-dir $D dashboard                    # -> dashboard.html
open $D/dashboard.html                                       # or: python -m http.server -d $D

Use it — Claude Code (MCP + skills)

1. Add the MCP server (see .mcp.json) and set JOBSEARCH_DATA to your folder.

2. In a Claude Code session in this repo, just ask: "find jobs", "apply to ", "make this application non-trivial", "build my dashboard". The skills in .claude/skills/ drive the backend; the MCP server (src/mcp_server.py) exposes the same as callable tools (get_profile, read_jobs, refresh_jobs, get_application_fields, generate_application, make_nontrivial, score_triviality, build_dashboard, list_companies).

What "non-trivial" means

A trivial application restates your CV in the form's fields — the axis an ATS reduces to keywords. A non-trivial one changes what the reader thinks they're hiring for: it reframes the role onto an axis where you win, carries a witness only you could produce (a short teardown of their product through your lens), and maps every claim to a real fact in your CV (the honesty gate — unbacked claims are flagged, never invented). See src/nontrivial.py and the make-nontrivial skill.

Tests

python -m tests.adversarial          # offline
python -m tests.adversarial --net    # + live ATS probes

Honest caveats

• Scraping ToS: Naukri/LinkedIn/Indeed prohibit automated scraping. For personal, low-volume use the practical risk is IP rate-limiting, not litigation — run modestly and pair with each board's own saved-search alerts. If a board returns nothing, it's likely a temporary block.

• Fetch failures are surfaced, never hidden. If a company's real form can't be loaded, the template is flagged fetch_failed and the dashboard shows a red banner — verify on the apply page.

• Salary/notice/relocation are marked TODO_CONFIRM and surfaced for review; the tool never guesses them.