io.github.tarunlnmiit/autopilot-jobhunt

Official

by tarunlnmiit · Python

Agentic job hunt: scan careers pages, score against your resume, draft applications. Never applies.

Scans job listings, scores matches against your resume, and drafts applications.

job searchresume matchingapplication draftingcareers page scrapingjob automation

Topics

ai-agentautomationclaudejob-searchllmmcpopenrouterpythoncareertelegram-bot

README.md13 KBView on GitHub

autopilot-jobhunt

Your AI job agent. Finds, scores, and drafts applications — while you sleep.

Scans 130+ company careers pages nightly → scores every role against your resume with an LLM → sends you the top matches on Telegram → drafts a tailored resume + cover letter on demand.

🔒 Drafts only — never applies. You review every draft and submit applications yourself. See PRIVACY.md for exactly what data leaves your machine.

Published on PyPI and listed on the Official MCP Registry (io.github.tarunlnmiit/autopilot-jobhunt), Glama (Quality A), and Smithery (MCPB bundle).

📖 Full setup guide with Claude Code MCP integration → SETUP.md

⭐ Star this repo if it helps you land a job

This tool is free, open source, and runs entirely on your machine — no subscription, no credit card. The only "payment" I ask: if it surfaces a role you apply to (or land), drop a star. It takes one click, costs you nothing, and it's the single thing that pushes the project in front of the next person grinding through 130 careers pages by hand. ⭐ Star it here →

How it works

mermaid

flowchart LR
    A["🌐 130+ Careers Pages"] -->|TinyFish API| B["Job Discovery"]
    B --> C["LLM Batch Scorer\n(0–100 fit score)"]
    C -->|score ≥ min| D["📱 Telegram Alert\nTop N matches"]
    C -->|on demand| E["✉️ Cover Letter\n+ Resume Bullets"]
    C --> F["📊 CSV Export"]

The scoring prompt uses your actual resume — not keywords. The LLM reads your full work history and the job description, then explains in one sentence why you fit or don't. No more guessing.

What a scan result looks like

code

Scanning Mistral AI...
  3 new job URLs. Fetching details...
  Scoring jobs...
  Saved 2 jobs from Mistral AI

Scanning HuggingFace...
  5 new job URLs. Fetching details...
  Scoring jobs...
  Saved 3 jobs from HuggingFace

Scanning Stripe...
  No new jobs found
...
Scan complete.
Top 5 sent to Telegram.

What the Telegram notification looks like

code

Job Hunt — 06 Jun 2026
5 matches found

#1 | Mistral AI | Applied AI Engineer, ML Infrastructure
📍 Paris/London/Marseille, On-site
🔧 Python, LLMs, RAG, AWS, MLOps, DevOps
✅ Role combines applied AI + ML infrastructure in EU, aligns with MLOps/RAG expertise and relocation goal
Score: 85/100  →  https://jobs.lever.co/mistral/...

#2 | HuggingFace | Staff ML Engineer
📍 Remote (EU)
🔧 Python, PyTorch, Transformers, CUDA, MLOps
✅ Open-source ML role matches deep learning and distributed training background
Score: 80/100  →  https://apply.workable.com/huggingface/...

...

Reply "apply to #N" to draft a tailored application.

What it does

code

Every night at 2:30 AM:
  ┌─────────────────────────────────────────────────────────┐
  │  Scans careers pages  →  Scores with LLM  →  Notifies  │
  │       (130+ cos)           (0–100 fit)       (Telegram) │
  └─────────────────────────────────────────────────────────┘

On demand:
  autopilot draft 1  →  tailored resume + cover letter in 60s

Usage modes

code

Mode 1: Standalone CLI (no Claude Code required)
  pip install autopilot-jobhunt
  autopilot scan / autopilot draft 1 / autopilot export

Mode 2: Claude Code MCP (control via natural language)
  pip install 'autopilot-jobhunt[mcp]'
  claude mcp add autopilot-jobhunt ...
  → "Scan for ML jobs" / "Draft application for job #2"

Both modes use the same config and produce the same output.

Quick start

Option A — pip install

bash

pip install autopilot-jobhunt        # or: pip install 'autopilot-jobhunt[mcp]' for Claude Code
mkdir my-job-hunt && cd my-job-hunt
autopilot init                       # creates config.json, companies.json, resume/, .env
# Fill in config.json (API keys + your profile) and resume/YOUR_RESUME.md, then:
autopilot scan

Option B — clone (recommended if you want to customize companies or contribute)

bash

git clone https://github.com/tarunlnmiit/autopilot-jobhunt.git
cd autopilot-jobhunt
pip install -e '.'               # standalone CLI
# pip install -e '.[mcp]'       # + Claude Code MCP integration
cp config.example.json config.json && cp .env.example .env
# Fill in your API keys and candidate profile, then:
autopilot scan

For the full walkthrough — API key setup, Claude Code MCP registration, rate limit details, and troubleshooting — see SETUP.md.

📚 Documentation

Step-by-step guides live in docs/:

Guide	Covers
Install	pip / from source / `autopilot init` scaffolding
LLM providers	OpenRouter fallback chain, Claude CLI (keyless), Anthropic API
API keys	TinyFish + OpenRouter keys, where each goes
Companies & scanning	`companies.json`, discovery + scoring, scan pacing
Integrations	Telegram notifications
MCP server & Skill	Drive the hunt from Claude Code
Config & scoring	Candidate profile, `min_score`, `top_n`
Troubleshooting	Every error we've hit, and the fix
Testing checklist	Reproducible independent verification

API keys needed

Service	Cost	Required	Where to get it
TinyFish	Free — no credit card	Always	agent.tinyfish.ai
OpenRouter	Free — 4-model fallback chain	Unless using Claude CLI / Anthropic	openrouter.ai
Telegram	Free	Optional	@BotFather on Telegram

Claude Code / MCP integration

Use autopilot-jobhunt as an MCP server inside Claude Code (CLI) or Claude Desktop.

Step 1: Install with MCP support

bash

git clone https://github.com/tarunlnmiit/autopilot-jobhunt.git
cd autopilot-jobhunt
pip install -e '.[mcp]'

Step 2: Register with Claude Code

Option A — one command:

bash

claude mcp add autopilot-jobhunt \
  --env TINYFISH_API_KEY=your_key \
  --env OPENROUTER_API_KEY=your_key \
  --env TELEGRAM_TOKEN=your_token \
  --env TELEGRAM_CHAT_ID=your_chat_id \
  -- python -m job_hunt.mcp_server

Option B — edit ~/.claude.json manually:

json

{
  "mcpServers": {
    "autopilot-jobhunt": {
      "command": "python",
      "args": ["-m", "job_hunt.mcp_server"],
      "cwd": "/absolute/path/to/autopilot-jobhunt",
      "env": {
        "TINYFISH_API_KEY": "your_key",
        "OPENROUTER_API_KEY": "your_key",
        "TELEGRAM_TOKEN": "your_token",
        "TELEGRAM_CHAT_ID": "your_chat_id"
      }
    }
  }
}

Note: cwd must point to the cloned repo — the server reads config.json and companies.json from there.

Step 3: Use it

In any Claude Code session:

code

"Scan for ML jobs"
"Draft an application for job #2"
"Export jobs from the last 7 days with score above 70"

Claude Desktop

Same JSON block — add it under mcpServers in Claude Desktop → Settings → Developer.

Customize your target companies

Edit companies.json. Each entry needs:

json

{
  "name": "Stripe",
  "careers_url": "https://stripe.com/jobs",
  "search_domain": "stripe.com",
  "location": "Remote / San Francisco, CA",
  "region": "Remote"
}

The repo ships with 130+ pre-configured EU, NZ, and remote-friendly tech companies. Add or remove as you like.

How scoring works

The LLM reads your full resume + the full job description and assigns a score 0–100:

Score	Meaning
80–100	Near-perfect fit — apply immediately
60–79	Good fit — worth applying
40–59	Partial fit — apply if pipeline is thin
< 40	Poor fit — skipped

Set min_score in config to filter. Default: 60.

Project structure

code

autopilot-jobhunt/
├── job_hunt/
│   ├── main.py          # CLI entry point
│   ├── scanner.py       # Job discovery + LLM scoring
│   ├── drafter.py       # Resume tailoring + cover letter
│   ├── notifier.py      # Telegram notifications
│   ├── llm_utils.py     # OpenRouter wrapper with fallback
│   ├── tools.py         # Protocol-agnostic tool layer
│   └── mcp_server.py    # MCP server (Claude/AI assistant integration)
├── demo/                # Demo scripts for recording GIF
├── resume/              # Put your resume here (gitignored)
├── state/               # Scan state (gitignored)
├── output/              # Generated applications (gitignored)
├── companies.json       # 130+ target companies
├── config.example.json  # Config template (copy to config.json — gitignored)
└── config.json          # Your config (gitignored — never committed)

LLM options

Default: OpenRouter (free)

Uses a 4-model fallback chain — all free, no credit card needed:

Model	Role
`meta-llama/llama-3.3-70b-instruct:free`	Primary — best quality
`nvidia/nemotron-3-super-120b-a12b:free`	Fallback 1 — 120B
`google/gemma-4-31b-it:free`	Fallback 2
`qwen/qwen3-coder:free`	Fallback 3

If one model hits its daily free-tier quota, the tool automatically tries the next. Zero LLM cost by default.

Alternative A: Claude Code CLI (no API key needed)

If you have Claude Code installed and authenticated, you can use it as the LLM backend — no separate API key required:

In config.json:

json

"llm_provider": "claude_cli"

Or via environment variable: LLM_PROVIDER=claude_cli autopilot scan

Optionally set a model: "claude_cli_model": "sonnet" (or "opus", "haiku", empty = Claude's default).

Note: Requires the claude binary in your PATH. Verify with claude --print "hi" first. The MCP server and cron jobs must run in an environment where your claude auth session is active.

Rate-limit note: Each call loads your global Claude Code context (~25–30k tokens). A nightly scan (5–15 LLM calls) burns significantly against your subscription's 7-day rate limit. Prefer OpenRouter for nightly automation; use Claude CLI for occasional on-demand drafts.

Alternative B: Anthropic API

If you have an Anthropic API key:

bash

pip install 'autopilot-jobhunt[claude]'

In config.json:

json

"llm_provider": "anthropic",
"anthropic_api_key": "sk-ant-...",
"anthropic_model": "claude-haiku-4-5-20251001"

claude-haiku-4-5-20251001 is fast and cheap; claude-sonnet-4-6 gives higher quality scores. A nightly scan uses ~5–15 LLM calls total (jobs scored in batches of 10).

Contributing

See CONTRIBUTING.md. PRs welcome for:

Adding companies to companies.json
New ATS platform support (Rippling, Lever variants, Workday)
OpenAI / Gemini MCP adapters
Better scoring prompts

License

MIT — see LICENSE.

Built by @tarunlnmiit. If this saved you hours of job searching, a ⭐ means a lot.

Install

claude_desktop_config.json

{
  "mcpServers": {
    "autopilot-jobhunt": {
      "command": "uvx",
      "args": [
        "autopilot-jobhunt",
        "mcp"
      ]
    }
  }
}