CleanJobData MCP Server

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

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.

Related MCP server: trackly-cli

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": ""
                 }
             }
         }
     }

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 (required): Your API key for accessing the CleanJobData API, sent as a Bearer token. The server needs this to make authenticated requests for job data.

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]'

2. Run tests:

pytest

Contributing

Contributions are welcome.

License

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