jobs-winterchill-mcp
An MCP server for searching UK tech jobs from the winterchill catalog, enabling job search, company lookup, and CV matching/tailoring via LLM agents.
README
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/jobsget_job→GET /api/v1/jobs/{source}/{id}get_company→GET /api/v1/companies/{key}match_cv→POST /api/cv/matchtailor_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
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