jobs-winterchill-mcp

An MCP server over the winterchill UK tech-jobs catalog (jobs.winterchill.xyz). It's a thin, read-only client over the public catalog API — no secrets, nothing stored — that lets an MCP client (Claude Desktop, the Claude CLI, etc.) search jobs, inspect companies, and match/tailor a CV.

Tools

| Tool | What it does | |------|--------------| | search_jobs | Search the live board (free-text + filters: city, salary, sponsorship, discipline, tech, level, source, sort). | | get_job | Fetch one job by source + id, with the full description. | | get_company | Company facts (rating, size, industry, Levels.fyi comp) + its current live roles. | | match_cv | Rank the live board against a pasted CV (semantic retrieve → rerank → comp-weighted). | | tailor_cv | ATS-tailor a CV to one job — returns applyable before → after edits + advice. | | list_filters | The accepted filter values (cities, disciplines, levels, sources, technologies). |

match_cv / tailor_cv are stateless and anonymous (nothing is stored); they're rate-limited per IP. tailor_cv returns up to 5 edits on the free/anonymous tier.

Install / configure

Requires Python ≥ 3.10. The server speaks MCP over stdio.

Add it to your MCP client config (Claude Desktop claude_desktop_config.json, or the Claude CLI):

{
  "mcpServers": {
    "winterchill": {
      "command": "uvx",
      "args": ["jobs-winterchill-mcp"]
    }
  }
}

Or run from a local checkout:

uv run jobs-winterchill-mcp
# or
pip install -e . && jobs-winterchill-mcp

Configuration

| Env var | Default | Purpose | |---------|---------|---------| | WINTERCHILL_API_BASE | https://jobs.winterchill.xyz | Override the catalog API base URL (e.g. for local dev). |

How it works

Every tool maps to a public endpoint:

• search_jobs → GET /api/v1/jobs
• get_job → GET /api/v1/jobs/{source}/{id}
• get_company → GET /api/v1/companies/{key}
• match_cv → POST /api/cv/match
• tailor_cv → POST /api/cv/job-match (mode: tailor)

No API key is needed. The catalog data is the same already-public board; this server just makes it available to LLM agents over MCP.

Releasing

Publishing to PyPI is automated via GitHub Actions + PyPI Trusted Publishing (OIDC, no token stored). In short: bump version in pyproject.toml, then publish a GitHub Release — the publish workflow builds and uploads. Full steps (incl. the one-time PyPI pending-publisher setup) are in RELEASING.md.

License

MIT © Valerii Iatsko