JustHireMe is a free, open-source, local-first AI job search workbench that allows you to collect job leads, filter low-quality postings, rank role fit, and generate role-specific application documents.
You can use it to replace noisy job-board browsing with a local pipeline that keeps resumes, profile data, lead history, vectors, generated PDFs, and settings on your device by default.
Features
- Collects job leads from ATS boards, RSS feeds, Hacker News, GitHub-style sources, Reddit and community boards, APIs, and custom-configured targets.
- Applies a deterministic quality gate to reject stale, thin, senior-only, unpaid, spammy, or missing-context postings before they enter the pipeline.
- Scores role alignment, stack coverage, project evidence, seniority fit, location constraints, red flags, source signal, and semantic profile similarity.
- Uses Kuzu graph data and LanceDB vector search to match jobs against your full profile context.
- Generates a tailored resume PDF, cover letter PDF, founder message, LinkedIn note, cold email, keyword coverage summary, and selected-project rationale for each strong lead.
- Stores all profile data, lead history, graph data, vector tables, generated PDFs, and settings locally.
- Exposes a local SQLite CRM for tracking leads through a review workflow.
- Includes an MCP server with three tools for scoring job fit, evaluating lead quality, and extracting company and stack intelligence from lead text.
- Accepts optional LLM-assisted evaluation on top of deterministic scoring when a model is configured.
- Supports Ollama for local models.
Use Cases
- Build a local job lead pipeline from multiple boards, feeds, communities, and configured targets.
- Filter weak job postings before they enter a serious application workflow.
- Rank roles against a resume, project history, skills, location needs, and seniority level.
- Generate a focused application package for a promising job lead.
- Maintain a private CRM for job opportunities, outreach drafts, and generated documents.
- Extend a job search workflow with custom source adapters and ranking logic.
- Connect an AI assistant to job-fit scoring through the included MCP server.
How to Use It
1. Download the latest JustHireMe app on the release page.
2. Launch the JustHireMe app and complete the setup wizard.
3. Add resume or profile data so the app can build profile context for ranking and document generation.
4. Configure app settings, API keys, local model options, and development overrides as needed.
5. Add or use job discovery sources such as ATS boards, company boards, feeds, communities, APIs, and configured targets.
6. Run lead ingestion so the app can normalize job postings before the quality gate checks them.
7. Review rejected leads and rejection reasons before you adjust source quality or ranking expectations.
8. Review accepted leads in the local CRM pipeline.
9. Open fit scores and ranking explanations before you spend time on an application.
10. Generate a resume PDF, cover letter PDF, founder message, LinkedIn note, cold email, keyword coverage summary, and selected-project rationale for strong leads.
11. Review every generated document before sending it.
MCP Server
JustHireMe includes a lightweight stdio MCP server at backend/mcp_server.py.
It exposes these tools:
| Tool | Purpose |
|---|---|
score_job_fit | Score a raw job posting against a candidate JSON profile. |
evaluate_lead_quality | Run the deterministic quality gate for a normalized lead. |
extract_lead_intel | Extract company, location, budget, urgency, stack, and signal quality from lead text. |
Install backend dependencies before starting the MCP server.
cd backend
uv sync --dev
cd ..Start the MCP server on Windows.
backend\.venv\Scripts\python.exe backend\mcp_server.pyStart the MCP server
backend/.venv/bin/python backend/mcp_server.pyUse this client configuration pattern with absolute paths.
{
"mcpServers": {
"justhireme": {
"command": "/absolute/path/to/JustHireMe/backend/.venv/bin/python",
"args": ["/absolute/path/to/JustHireMe/backend/mcp_server.py"],
"cwd": "/absolute/path/to/JustHireMe"
}
}
}Windows users should point the command value to this interpreter path.
backend\\.venv\\Scripts\\python.exeAgent Skills
Point your AI coding assistant at skills/justhireme/SKILL.md inside the repository to load the included agent skill. It works with Claude, Codex, IDE agents, and custom agent runners with no runtime dependency on any specific API.
Related Resources
- JustHireMe: Official project site.
- JustHireMe Architecture Docs: Desktop, backend, and local data architecture.
- JustHireMe Source Adapter Docs: Adapter rules and normalized lead structure.
- JustHireMe MCP Docs: MCP server setup and available tools.
- Best Open Source AI Coding Agents
Pros
- Free AGPL open-source core.
- Local-first job data.
- Explainable ranking rules.
- Profile-aware matching.
- Built-in document generation.
- MCP server and Agent Skills included.
Cons
- Full setup requires Node.js 24, Python 3.13, Rust, and uv.
- Windows is the only primary stable installer target.
- macOS and Linux are CI build paths.
- No mobile or browser-based access.
FAQs
Q: Is JustHireMe free?
A: JustHireMe is free and open source under the AGPL-3.0 license. Organizations that need private forks, proprietary changes, embedding, white-labeling, or managed deployments need the commercial license path.
Q: Does JustHireMe require a sign-up?
A: JustHireMe runs as a local desktop workbench, so the core workflow centers on installation and local configuration. Access to external AI models requires a separate API key from the model provider.
Q: Does JustHireMe automatically apply to jobs?
A: JustHireMe contains browser automation and auto-apply code, but that area remains experimental, opt-in, and unsupported as the stable workflow.
Q: What application files can JustHireMe generate?
A: JustHireMe can generate a resume PDF, cover letter PDF, founder message, LinkedIn note, cold email, keyword coverage summary, and selected-project rationale for a selected job lead.
Q: Is JustHireMe a good ApplyPilot alternative?
A: JustHireMe is good for users who want local-first job intelligence, explainable ranking, and manual review. ApplyPilot fits users who want a stronger focus on autonomous job application behavior.
