Workforce Data Explorer

Workforce Data Explorer

One interface for 89 curated US workforce and labor market data sources — 30 with live API access spanning official statistics (BLS, FRED, Census, O*NET, DOL, SEC EDGAR) and real-time signals (Indeed Hiring Lab job postings, ADP payrolls, the Anthropic Economic Index).

Three ways to use it, easiest first:

| | What | Where | |---|---|---| | 🖥️ | Live dashboard — browse, chart, download. Zero setup. | workforce-data-explorer.streamlit.app | | 🤖 | AI connector (MCP) — ask your own Claude or ChatGPT questions answered with live labor data | https://workforce-data-mcp.onrender.com/mcp | | ⚙️ | Run it yourself — clone this repo, bring free API keys | [Quick start](#run-it-yourself) below |

What's inside

| Source | What you get | |---|---| | FRED | 816,000+ time series — unemployment, job openings, quits, wages, participation, claims, CPI, GDP | | BLS | CES payrolls, CPS household survey, JOLTS, Employment Cost Index, productivity, OEWS occupation wages | | Census | ACS demographics/income/commuting by state & county, QWI hires/separations, County Business Patterns | | **ONET | 900+ occupation profiles — skills, tasks, abilities, technology used | | DOL | Weekly UI claims, OSHA inspections, wage & hour enforcement | | SEC EDGAR | Layoff 8-Ks, human capital disclosures from 10-Ks, filings by company | | Indeed Hiring Lab | Daily job postings indexes (national/state/metro/sector) + AI-postings share | | ADP | Weekly and monthly private payrolls (via FRED) | | Anthropic Economic Index* | Real-world AI usage by occupation and task |

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🖥️ The dashboard

workforce-data-explorer.streamlit.app — nothing to install.

• Catalog — search all 89 curated sources by topic
• Job Postings — real-time labor demand from Indeed, incl. AI's share of postings
• State Labor Markets — the four headline indicators for any state
• **FRED / BLS / Census / ONET / DOL / SEC pages* — fetch, chart, and download any series as CSV
• AI Assistant — ask questions in plain English ("show me quits vs. openings

since 2022"). The shared assistant allows a few questions per minute; paste your own free Groq key into the expander on that page for unlimited use.

🤖 The AI connector (MCP)

The best experience: plug live labor data into the AI you already use. The connector exposes 15 tools — FRED and BLS series, occupation wages, Census ACS, O*NET occupations, UI claims, SEC layoff/company filings, Indeed daily job postings, AI-postings share, state labor market snapshots, and AI-usage exposure by occupation — and your AI decides which to call.

Claude (claude.ai) — requires a paid plan:

1. Settings → Connectors → Add custom connector
2. Name: Workforce Data — URL: https://workforce-data-mcp.onrender.com/mcp
3. In a new chat, ask something like *"What's happening with layoffs at public

companies this month?" or "Compare software developer and nurse wages."*

ChatGPT — Settings → Connectors (developer mode) → add the same URL.

Claude Desktop app, running locally — the easy way is the extension bundle:

1. Clone the repo and create the venv (see [Run it yourself](#️-run-it-yourself)).
2. Download Workforce-Data.mcpb from the

latest release and double-click it.

1. Claude opens an install dialog — click Install, then point it at your

cloned repo folder when asked. The connector appears in Settings → Extensions with an on/off toggle. Done — no config files.

Alternative: manual claudedesktopconfig.json entry

> ⚠️ Edit this file only while Claude is fully quit (⌘Q). The app rewrites > it from memory on exit, so edits made while it's running are silently lost.

{
  "mcpServers": {
    "workforce-data": {
      "command": "/path/to/workforce-data/.venv/bin/python",
      "args": ["/path/to/workforce-data/mcp_server.py"]
    }
  }
}

Claude Code — one command, available in every session:

claude mcp add --scope user workforce-data -- /path/to/workforce-data/.venv/bin/python /path/to/workforce-data/mcp_server.py

> The hosted connector runs on a free tier that sleeps when idle — the first > question after a quiet spell takes ~30–60 seconds while it wakes up.

⚙️ Run it yourself

Requires Python 3.10+ (tested on 3.13). All dependencies are in requirements.txt.

git clone https://github.com/thelancehaun/workforce-data-explorer.git
cd workforce-data-explorer
python -m venv .venv && source .venv/bin/activate   # Windows: .venv\Scripts\activate
pip install -r requirements.txt
cp .env.example .env   # then add your free API keys (see below)

streamlit run app.py            # the dashboard
python mcp_server.py            # the MCP server (stdio, for Claude Desktop)
python mcp_server.py --http     # the MCP server (HTTP, for remote hosting)

The app runs without any keys — SEC, O*NET, and parts of BLS/Census work keyless — but FRED (which powers most time series) and the AI Assistant chat need free ones.

API keys (all free, ~5 minutes total)

| Key | Powers | Get it at | |---|---|---| | FRED_API_KEY | Most time series | fred.stlouisfed.org | | BLS_API_KEY | Higher BLS rate limits | data.bls.gov | | CENSUS_API_KEY | ACS / QWI / CBP queries | api.census.gov | | GROQ_API_KEY | In-app AI Assistant chat | console.groq.com | | DOL_API_KEY | OSHA / WHD enforcement data | dataportal.dol.gov | | ONET_API_KEY | Optional — higher O*NET limits | services.onetcenter.org |

Deploy your own copies

• Dashboard → Streamlit Community Cloud (free):

point it at your fork, paste your keys under app Settings → Secrets.

• MCP server → Render (free): the included

render.yaml configures it — connect your fork as a Blueprint and add your keys as environment variables. Any Python host (Fly.io, Railway, a VPS) works too: python mcp_server.py --http.

Architecture

app.py                    Streamlit dashboard (Overview, AI Assistant, data pages)
ui_theme.py               Shared chart styling (validated palette, light/dark)
mcp_server.py             MCP server (stdio + streamable HTTP, TTL-cached tools)
workforce_data/
  catalog.py              Searchable metadata for 89 curated sources
  chat.py                 Tool-calling chat engine (Groq) + shared tool layer
  sources/
    fred.py bls.py census.py onet.py dol.py sec.py indeed.py aei.py

Fetched data is cached in memory in both apps (1 hour for time series, up to a day for searches and metadata), so repeat queries don't burn API quota.

Bugs, ideas, and working together

• Bug or wrong-looking data?

Open an issue — templates make it quick.

• Want to suggest a data source? Same place — there's a template for that.
• Working together / press: the contact link is on the app's

About page (kept off GitHub so scrapers don't get it).

License

MIT — see [LICENSE](LICENSE).

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: thelancehaun
• Source: thelancehaun/workforce-data-explorer
• License: MIT

Install and usage instructions live in the source repository linked above.