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io.github.DeJo90/nace-mcp

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

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About io.github.DeJo90/nace-mcp

io.github.DeJo90/nace-mcp is an MCP server in the Search category: browse, search and fuzzy-match NACE Rev. 2.1 economic activity classification codes.

Install

Claude Code
claude mcp add io-github-dejo90-nace-mcp -- npx -y nace-mcp
npx
npx -y nace-mcp

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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README

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

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About io.github.DeJo90/nace-mcp

How do I install io.github.DeJo90/nace-mcp?

Run claude mcp add io-github-dejo90-nace-mcp -- npx -y nace-mcp, then add the server to your MCP client's configuration.

Is io.github.DeJo90/nace-mcp safe to use with an AI agent?

Its trust score is 37 out of 100 (low). It passes 1 of the 1 static security checks run so far. It has no ConduID identity yet, so agent calls to it are not receipted.

Is io.github.DeJo90/nace-mcp still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.