jobdatapool-mcp 0.1.0

MCP server for JobDataPool job search, source provenance, and analyst workflows

jobdatapool-mcp

A local Model Context Protocol server for JobDataPool job listings, source provenance, dataset QA, company briefs, and market scans.

This Python package is a parity-oriented port of the Node JobDataPool MCP surface. It exposes the same six core tools, three resources, and three guided prompts described on the JobDataPool MCP page.

Requirements

• Python 3.10+
• An MCP-compatible client that can launch a local stdio server, such as Claude Desktop, Claude Code, Cursor, or Windsurf

Install

pip install jobdatapool-mcp

Run locally

jobdatapool-mcp

The server uses https://jobdatapool.com by default.

For local site testing, point it at your local JobDataPool build:

JOBDATAPOOL_BASE_URL=http://localhost:8888 jobdatapool-mcp

The dataset snapshot is cached for 10 minutes by default. Override that with:

JOBDATAPOOL_CACHE_TTL_SECONDS=60 jobdatapool-mcp

MCP client config

Claude Desktop / Claude Code / Cursor / Windsurf

After installing from PyPI, use the package command directly:

{
  "mcpServers": {
    "jobdatapool": {
      "command": "jobdatapool-mcp",
      "env": {
        "JOBDATAPOOL_BASE_URL": "https://jobdatapool.com"
      }
    }
  }
}

For a local checkout before publishing, run through Python instead:

{
  "mcpServers": {
    "jobdatapool": {
      "command": "python",
      "args": ["-m", "jobdatapool_mcp.server"],
      "cwd": "/absolute/path/to/jobdatapool-mcp",
      "env": {
        "JOBDATAPOOL_BASE_URL": "https://jobdatapool.com"
      }
    }
  }
}

Tools

search_jobs

Search the current JobDataPool snapshot by keyword and filters.

Useful arguments include:

• query
• limit
• location
• country
• company
• industry
• skill
• seniority
• employment_type
• remote
• posted_within_days
• salary
• sort

Example prompts:

Find remote senior Python security jobs in the US.

Search JobDataPool for data engineering roles in healthcare, limit to 15, and include listing ids.

Find remote product manager jobs with salary signals and summarize the strongest matches.

get_job

Return one listing by JobDataPool id. Raw source and application URLs are masked; results include the JobDataPool redirect handoff URL when an id is available.

Tell me more about listing id 12345.

get_company

Summarize a company footprint from matching listings in the current snapshot.

Brief me on Huntress in the current JobDataPool snapshot.

The response includes matching listing count, locations, seniority, industries, skills, examples, and snapshot caveats.

get_filter_options

Show high-count facet values for common filters.

What skills, countries, locations, industries, and companies are common in this dataset?

find_similar_jobs

Find listings similar to a known JobDataPool listing id using title, skill, company, industry, and summary overlap.

Find jobs similar to listing id 12345.

get_sources

Return the JobDataPool source catalog, contract pointers, and local MCP cache status.

What snapshot is this MCP reading, and how many rows are cached?

Resources

• jobdatapool://source-catalog — live /v1/sources catalog plus cache status
• jobdatapool://analyst-context — dataset scope, cache behavior, provenance guidance, caveats, and URL masking policy
• jobdatapool://contracts — OpenAPI, schema, dataset, v1 endpoint, tool, resource, and prompt pointers

Prompts

• jobdatapool_market_scan(topic, location, remote) — role, skill, industry, or hiring-theme scan
• jobdatapool_company_brief(company) — company footprint summary workflow
• jobdatapool_dataset_qa() — source/catalog health and facet coverage workflow

URL masking behavior

The server does not return raw source or application URLs. It removes common origin URL fields and replaces embedded external URLs in scraped text with [masked external URL]. When a JobDataPool id is present, outputs include:

https://jobdatapool.com/jobrd?id=<id>

Publishing

This repository is wired for PyPI Trusted Publishing through GitHub Actions. Configure a PyPI Trusted Publisher for the repository and the release environment, then push a tag:

git tag v0.1.0
git push origin v0.1.0