Eurostat TAM MCP server

Eurostat TAM MCP server

Pulls enterprise counts by NACE Rev.2 activity and size class from Eurostat and buckets them into SME and 250+ categories for the DTM TAM model, with tools to fill TAM spreadsheets directly.

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Eurostat TAM MCP server

An MCP server that pulls enterprise counts by NACE Rev.2 activity and size class from Eurostat (dataset sbs_sc_ovw) and buckets them to match the DTM TAM model's columns:

Sheet column What this server returns
SMEs sme_count — enterprises with 1–249 employees (optionally excl. micro 0–9)
Corp: Mid-cap (250–4,999) corp_250plus_countall 250+ firms*

* Eurostat's top size band is 250+ with no 5,000 split, so use ORBIS/ONS to separate Mid-cap from Large downstream.

What this does NOT cover (by design — the model sources these elsewhere)

  • Startups / Scaleups → Dealroom / Harmonic (venture-backed, € raised)
  • Corp Large (5,000+) → ORBIS / UK ONS
  • United Kingdom → ORBIS / ONS (UK left Eurostat after Brexit)

Default geography is EU27 + Norway + Switzerland, summed (EU27 via Eurostat's pre-aggregated EU27_2020 geo, so one call covers all 27).

Tools

get_enterprise_counts(nace_code, geo?, year?, exclude_micro?)

One NACE code → SME and 250+ counts. Example: get_enterprise_counts("C27").

get_segment_counts(nace_codes, geo?, year?, exclude_micro?)

A list of codes for one value-chain segment → per-code results plus a summed segment total. Example for "Equipment Suppliers & OEMs": get_segment_counts(["C27", "C28"]).

fill_tam_sheet(input_path, output_path?, dry_run=True, geo?, year?, exclude_micro?)

Reads NACE codes straight from the Company Counts by Segment sheet, pulls counts for every segment, and writes the SMEs (col F) and Corp Mid-cap 250+ (col G) cells. Run with dry_run=True first to audit the per-row parse, then dry_run=False to save (defaults to <input>_FILLED.xlsx — never overwrites the original unless you pass the same path).

Only yellow input cells are written; blue subtotals, the grey public-sector row, and demand-side rows are left untouched. Subtotal/Low/High formulas and cell formatting are preserved.

A critical data caveat: Eurostat has no 4-digit NACE detail

sbs_sc_ovw only goes down to division (C27) and group (C279) — there is no class-level data (C26.30, D35.11, …). The CMO's sheet is mostly class codes, so every code is resolved down to the nearest level that exists:

class → group → division → section

Each row reports which codes it used and a coarsened list flagging where it fell back to a whole division (e.g. J63 = all information services). Those numbers are upper bounds for the intended class — refine with ORBIS if needed.

NACE sub-classes use the dotted form in the sheet, e.g. "C26.30", "D35.11".

Setup

cd /Users/lini/Documents/Claude/eurostat-mcp
uv venv --python 3.12
uv pip install "mcp[cli]"

Test the live logic without the MCP layer:

uv run python -c "import server, json; print(json.dumps(server.get_enterprise_counts('C27'), indent=2))"

Register it with Claude Code

Copy the block in .mcp.json into your Claude Code MCP config, or from any project run:

claude mcp add eurostat-tam -- uv run --directory /Users/lini/Documents/Claude/eurostat-mcp server.py

Then in a Claude Code session you can just ask:

"Use eurostat-tam to pull C27+C28 for the Equipment Suppliers segment, exclude micro."

Notes & caveats

  • Summing NACE codes can double-count a firm that reports under multiple activities. De-dup per the sheet's classification waterfall before trusting totals.
  • Subtract venture-backed firms (counted as startups/scaleups) from the SME/Corp pulls so each company lands in exactly one bucket.
  • Latest year auto-resolves (currently 2024) unless you pass year.

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