MCP server for the CleanJobData Job API https://cleanjobdata.com
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Publish the container image to GHCR (#2)
Adds a Container Image workflow that builds linux/amd64 + linux/arm64 and
pushes to ghcr.io/jhgaylor/cleanjobdata-mcp.

Kept separate from the release workflow on purpose: that one carries the
PyPI publish, and a manual re-run there would try to re-upload an existing
version. This workflow can be dispatched against any ref safely, so an
image can be published for an existing tag without cutting a release:

    gh workflow run docker.yml --ref v0.2.0

Tags: `latest` and `X.Y.Z`/`X.Y` on release tags, `edge` on main, plus
`sha-<short>` everywhere. Pull requests build and smoke-test but never
push, so a fork cannot publish an image.

Every build boots the image and asserts /healthz and a tools/list call
over the MCP endpoint before anything is pushed.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-08-05 16:51:51 -04:00
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.gitignore Initial release of CleanJobData MCP Server 2026-08-05 00:06:51 -04:00
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CleanJobData MCP Server

A Model Context Protocol (MCP) server providing tools to interact with the CleanJobData Job API.

PyPI License: MIT

It runs two ways:

  • stdio (default) — your MCP client launches it locally and it uses the CLEANJOBDATA_API_KEY env var.
  • HTTP (--transport http) — one hosted server, many users, each authenticating with their own CleanJobData key sent per request. See Running as a remote HTTP server.

Available MCP Interactions

This server exposes the following MCP interactions:

Tools

  • search_jobs: Search for jobs using the CleanJobData API based on various criteria.
    • Parameters: title, sort_by, city_id, state_id, country_id, location, remote, remote_type, company_name, employer_id, salary_min, salary_max, require_salary, experience_level, employment_type, published_after, max_age, include_expired, include_description, limit, cursor, count.
  • get_job: Retrieve detailed information about a specific job (including its full description) by ID.
    • Parameters: job_id.
  • search_companies: Search for companies by name (fuzzy), website domain, or company IDs.
    • Parameters: query, website_url, employer_id, active, limit, offset.
  • get_company: Retrieve detailed information about a specific company, including enrichment data.
    • Parameters: company_id.
  • suggest_locations: Autocomplete city/state/country names into the IDs used by search_jobs geo filters.
    • Parameters: query, kinds, limit.

Prompts

  • create_candidate_profile: Generates a structured prompt based on candidate details (name, LinkedIn, website, resume text) to help guide job searching.
    • Parameters: name, linkedin_url, personal_website, resume_text.

Client Setup (Examples: Claude Desktop, Cursor)

To use this server with an MCP client like Claude Desktop or Cursor, you need to configure the client to run the server process and provide the CleanJobData API key.

  1. Ensure uv is installed: curl -LsSf https://astral.sh/uv/install.sh | sh

  2. Obtain a CleanJobData API Key: Request a key from CleanJobData. Set it as the CLEANJOBDATA_API_KEY environment variable.

  3. Configure your client:

    • Using uvx:

      • Claude Desktop: Edit your claude_desktop_config.json:
        {
          "mcpServers": {
            "cleanjobdata": {
              "command": "uvx",
              "args": [
                "cleanjobdata-mcp"
              ],
              "env": {
                "CLEANJOBDATA_API_KEY": ""
              }
            }
          }
        }
        
      • Cursor: Go to Settings > MCP > Add Server:
        • Mac/Linux Command: uvx cleanjobdata-mcp
        • Windows Command: cmd
        • Windows Args: /c, uvx, cleanjobdata-mcp
        • Set the CLEANJOBDATA_API_KEY environment variable in the appropriate section.
    • Running from source (Alternative):

      1. Clone the repo and note where you clone it to
      2. Claude Desktop: Edit your claude_desktop_config.json:
      {
          "mcpServers": {
              "cleanjobdata": {
                  "command": "uv",
                  "args": [
                      "run",
                      "--directory",
                      "PATH_TO_REPO",
                      "cleanjobdata-mcp"
                  ],
                  "env": {
                      "CLEANJOBDATA_API_KEY": ""
                  }
              }
          }
      }
      

Running as a remote HTTP server

The HTTP transport serves many users from a single process. Each request carries its own CleanJobData API key, so the server holds no user credentials and every upstream call is billed to the caller who made it.

cleanjobdata-mcp --transport http --host 0.0.0.0 --port 8000

The MCP endpoint is POST /mcp (streamable HTTP); GET /healthz is an unauthenticated liveness probe.

How clients authenticate

A client sends its key on every request, in either header:

Authorization: Bearer <cleanjobdata-api-key>
X-CleanJobData-API-Key: <cleanjobdata-api-key>

X-CleanJobData-API-Key wins if both are present. A request with neither is rejected with a message telling the caller how to supply one — it does not silently fall back to the server's own key.

Example client config (Claude Desktop / Cursor remote MCP server):

{
  "mcpServers": {
    "cleanjobdata": {
      "url": "https://your-host.example.com/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_CLEANJOBDATA_API_KEY"
      }
    }
  }
}

Or from the command line:

npx mcp-remote https://your-host.example.com/mcp --header "Authorization: Bearer YOUR_KEY"

Docker

Prebuilt images are published to GitHub Container Registry for linux/amd64 and linux/arm64:

docker run --rm -p 8000:8000 ghcr.io/jhgaylor/cleanjobdata-mcp:latest
Tag Points at
latest The most recent release
0.2.0, 0.2 That specific release / its latest patch
edge The tip of main
sha-<short> A specific commit

Or build it yourself:

docker build -t cleanjobdata-mcp .
docker run --rm -p 8000:8000 cleanjobdata-mcp

The image ships no API key — keys arrive per request. It defaults to MCP_TRANSPORT=http, HOST=0.0.0.0, PORT=8000, and runs as a non-root user.

Scaling out

Requests are stateless by default, so you can run several replicas behind a load balancer with no sticky sessions. To use your own ASGI server with multiple workers:

uvicorn cleanjobdata_mcp.app:app --host 0.0.0.0 --port 8000 --workers 4

Pass --stateful (or MCP_STATEFUL=1) only if you need per-session server state; that requires sticky routing.

Single-tenant HTTP deployments

If you want one hosted server that always uses your key rather than the caller's, set both CLEANJOBDATA_API_KEY and CLEANJOBDATA_ALLOW_ENV_KEY_FALLBACK=true. Requests that supply their own key still use it; requests without one fall back to the server's key. Leave this off for anything multi-user — otherwise a user who forgets their header gets billed to you.

CLI options

Flag Env var Default Purpose
--transport MCP_TRANSPORT stdio stdio or http
--host HOST 127.0.0.1 Bind address (use 0.0.0.0 in a container)
--port PORT 8000 Bind port
--path MCP_PATH /mcp URL path of the MCP endpoint
--json-response MCP_JSON_RESPONSE off Plain JSON instead of SSE, for proxies that buffer
--stateful MCP_STATEFUL off Keep per-session state in memory
--allowed-host MCP_ALLOWED_HOSTS none Allowed Host values; setting any enables DNS-rebinding protection
--allowed-origin MCP_ALLOWED_ORIGINS none Allowed Origin values

Operational notes

  • Terminate TLS in front of the server (load balancer, reverse proxy, or platform ingress). Keys travel in request headers, so plain HTTP over the public internet would expose them.
  • Tool handlers run in a thread pool, so a slow upstream call blocks one thread rather than the whole event loop. Very high concurrency benefits from more replicas rather than one large process.

Development

This project uses:

  • uv for dependency management and virtual environments
  • ruff for linting and formatting
  • hatch as the build backend

Common Tasks

# Setup virtual env
uv venv

# Install dependencies
uv pip install -e .

# install cli tools
uv tool install ruff

# Run linting
ruff check .

# Format code
ruff format .

Environment Variables

  • CLEANJOBDATA_API_KEY: Your API key for the CleanJobData API, sent upstream as a Bearer token. Required for stdio; over HTTP the caller's own header supplies the key instead.
  • CLEANJOBDATA_ALLOW_ENV_KEY_FALLBACK: Set to true to let HTTP requests without a key fall back to CLEANJOBDATA_API_KEY. Off by default — see Single-tenant HTTP deployments.
  • CLEANJOBDATA_API_BASE: Override the API base URL (default https://api.cleanjobdata.com).

Transport settings (MCP_TRANSPORT, HOST, PORT, …) are listed under CLI options.

Testing

This project uses pytest for testing the core tool logic. Tests mock external API calls using unittest.mock.

  1. Install test dependencies:
# Ensure you are in your activated virtual environment (.venv)
uv pip install -e '.[test]'
  1. Run tests:
pytest

Contributing

Contributions are welcome.

License

This project is licensed under the MIT License - see the LICENSE file for details.