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Nace MCP

by DeJo90version 1.0.1i★ –iRuns on your computer
Registry nameio.github.DeJo90/nace-mcp

Install

Overview

Description from the maker (original English)

Browse, search and fuzzy-match NACE Rev. 2.1 economic activity classification codes.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "nace": {
      "command": "npx",
      "args": [
        "-y",
        "nace-mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add nace -- npx -y nace-mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "nace": {
      "command": "npx",
      "args": [
        "-y",
        "nace-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "nace": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "nace-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account DeJo90, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

  • More stars than 0% of the other 7282 servers in this category
  • Published to the registry more recently than 3% of the other 7282 servers in this category
  • Basic checks equal to or better than 100% of the other 7282 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Nace MCP safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.0.1) reached the registry 9 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

nace-mcp

An MCP server exposing NACE Rev. 2.1 economic activity classification codes for AI agents.

NACE (Nomenclature of Economic Activities) is the European standard for classifying economic activities. This server loads all 1,047 codes into memory at startup and provides four tools for browsing, looking up, searching, and fuzzy-matching codes — without ever dumping the full dataset to the agent.

MCP Configuration

Add to your Claude (or any MCP-compatible client) config:

{

"mcpServers": { "nace-mcp": { "command": "npx", "args": ["nace-mcp"] } } }

Tools

nace_get(code)

Returns full details for a single NACE code.

Input: code — e.g. "A", "01", "25.1", "25.11"

Example output:

{

"code": "95.31", "label": "Repair and maintenance of motor vehicles", "level": "class", "parent": "95.3" }


nace_browse(parent_code?)

Returns the direct children of a code (compact: code + label only). Omit parent_code to list all 22 top-level sections. Max 50 results.

Input: parent_code (optional) — e.g. "C", "25", "25.1"

Example — `nace_browse()` (no argument):

[

{ "code": "A", "label": "Agriculture, forestry and fishing" }, { "code": "B", "label": "Mining and quarrying" }, { "code": "C", "label": "Manufacturing" }, ... ]

Example — `nace_browse("J")`:

[

{ "code": "58", "label": "Publishing activities" }, { "code": "59", "label": "Motion picture, video and television programme production, sound recording and music publishing activities" }, { "code": "60", "label": "Programming, broadcasting, news agency and other content distribution activities" }, ... ]


nace_search(query)

Case-insensitive substring search across all activity labels. Returns up to 10 matches.

Input: query — e.g. "software", "fishing", "consulting"

Example — `nace_search("software")`:

[

{ "code": "58.1", "label": "Publishing of books, newspapers and other publishing activities, except software publishing", "level": "group" }, { "code": "58.19", "label": "Other publishing activities, except software publishing", "level": "class" }, { "code": "58.2", "label": "Software publishing", "level": "group" }, { "code": "58.29", "label": "Other software publishing", "level": "class" } ]


nace_suggest(activity_description)

Fuzzy-matches a free-text description to NACE codes. Tokenizes the input, scores by matched terms, and returns the top 5 candidates with a brief explanation. Designed for AI agents doing classification.

Input: activity_description — free-text description of the economic activity

Example — `nace_suggest("computer programming software development consultancy")`:

[

{ "code": "62", "label": "Computer programming, consultancy and related activities", "level": "division", "reason": "Matched: \"computer\", \"programming\", \"consultancy\"" }, { "code": "62.1", "label": "Computer programming activities", "level": "group", "reason": "Matched: \"computer\", \"programming\"" }, { "code": "62.10", "label": "Computer programming activities", "level": "class", "reason": "Matched: \"computer\", \"programming\"" }, ... ]

Tip: For non-English descriptions (e.g. German "KFZ Mechaniker"), rephrase in English before calling nace_suggest.


Prompt Examples

These examples show how an AI agent uses the tools in practice.


"What NACE code applies to a car repair shop?"

The agent calls nace_suggest with an English description:

nace_suggest("motor vehicle repair maintenance workshop")
[

{ "code": "95", "label": "Repair and maintenance of computers, personal and household goods, and motor vehicles and motorcycles", "level": "division", "reason": "Matched: \"motor\", \"vehicle\", \"repair\", \"maintenance\"" }, { "code": "95.3", "label": "Repair and maintenance of motor vehicles and motorcycles", "level": "group", "reason": "Matched: \"motor\", \"vehicle\", \"repair\", \"maintenance\"" }, { "code": "95.31", "label": "Repair and maintenance of motor vehicles", "level": "class", "reason": "Matched: \"motor\", \"vehicle\", \"repair\", \"maintenance\"" } ]

The agent then drills into the best match with nace_get("95.31") to confirm the parent chain:

{

"code": "95.31", "label": "Repair and maintenance of motor vehicles", "level": "class", "parent": "95.3" }

Result: 95.31 is the correct class-level code for a car repair shop.


"What NACE code covers a bakery?"
nace_suggest("bakery bread pastry production")
[

{ "code": "10.71", "label": "Manufacture of bread; manufacture of fresh pastry goods and cakes", "level": "class", "reason": "Matched: \"bread\", \"pastry\"" } ]

Result: 10.71 — first candidate is an exact match, no further navigation needed.


"Explore the information & communication sector"

The agent browses the hierarchy top-down:

nace_browse("J")
[

{ "code": "58", "label": "Publishing activities" }, { "code": "59", "label": "Motion picture, video and television programme production, sound recording and music publishing activities" }, { "code": "60", "label": "Programming, broadcasting, news agency and other content distribution activities" }, { "code": "61", "label": "Telecommunications" }, { "code": "62", "label": "Computer programming, consultancy and related activities" }, { "code": "63", "label": "Information service activities" } ]

Then zooms into division 62:

nace_browse("62")
[

{ "code": "62.1", "label": "Computer programming activities" }, { "code": "62.2", "label": "Computer consultancy and computer facilities management activities" }, { "code": "62.3", "label": "Computer facilities management activities" }, { "code": "62.9", "label": "Other information technology and computer service activities" } ]


Data

  • Source: jnsprnw/nace-codes — community-maintained JSON conversion of the official Eurostat NACE Rev. 2.1 classification
  • Coverage: 1,047 entries across 22 sections (A–U), 4 levels (section → division → group → class)
  • Authority: Eurostat NACE Rev. 2.1

Development

npm install

npm run build # compile TypeScript → dist/ node dist/index.js # run the server (listens on stdio)

To inspect with the MCP Inspector:

npx @modelcontextprotocol/inspector node dist/index.js
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