UNdata
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@UNdatacompare Peru and Colombia GDP per capita"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
UNdata
CLI and MCP server for the UNdata SDMX REST API — UN Statistics Division open data. Query World Development Indicators, Millennium Development Goals and other UN datasets from your terminal, from analysis pipelines, or from any MCP client (Claude, Antigravity). No API key required.
Features
undataCLI — terminal access withtable/json/csv/parquetoutput, runnable from anywhereFull CLI ↔ MCP parity: the 7 tools, 3 prompts, and 3 reference docs are all reachable from both interfaces
7 MCP tools: list dataflows, WDI data, country profile, series search, MDG data, generic query, multi-country compare
3 prompts: economic analysis, development goals progress, country comparison — also via
undata prompt3 resources: API guide, country codes, WDI series catalog — also via
undata guide|countries|catalogDisk cache so repeated research queries are instant across runs
Declarative dataflow registry — add a dataset with one entry, no new code
Built for humans and AIs: pretty tables + Markdown for people; clean JSON/CSV and
--rawfor agents and pipelines
Related MCP server: unicefstats-mcp
Install (one command)
Requires uv. Installs both undata (CLI) and undata-mcp (server) onto your PATH.
# Windows (PowerShell)
./install.ps1 # add -Export for Parquet support
# macOS / Linux
./install.sh # add --export for Parquet supportOr directly:
uv tool install . # or: uv tool install '.[export]'After uv tool install, both commands live in uv's tool bin (e.g. ~/.local/bin), which uv puts on
your PATH — so undata and undata-mcp run from any directory. If your shell can't find them yet,
run uv tool update-shell and reopen the terminal.
Run without installing:
uvx --from . undata wdi PERPyPI (future): the package is metadata-complete and ready to publish. Once published, install anywhere with
pipx install undata-mcp/uvx undata-mcp. Publishing is a deliberate, public step (uv build && uv publish) and is intentionally left for you to trigger.
CLI usage
undata dataflows # list available datasets (live)
undata datasets # registered datasets + aliases (offline)
undata wdi PER --years 2015:2023 # WDI for one country
undata wdi PER --series NY_GDP_PCAP_CD --format table
undata profile PER --year 2022 # latest snapshot, all indicators
undata search education --country BRA # find WDI series codes
undata mdg PER --years 2000:2020 # Millennium Development Goals
undata compare PER COL BRA --series NY_GDP_PCAP_CD # multi-country comparison
undata compare PER COL --format csv -o out.csv # export to CSV for analysis
undata compare PER COL --format parquet -o out.parquet
undata query wdi A..PER --years 2020:2023 # generic SDMX query (alias or id)
# Reference docs (same content the MCP serves as resources)
undata guide # API guide (Markdown in a terminal, raw when piped)
undata countries --raw # ISO-3 country codes
undata catalog # common WDI series codes by topic
# Guided analysis prompts (same templates the MCP exposes)
undata prompt # list prompts
undata prompt country_economic_analysis -c PER --year 2022
undata prompt compare_countries -c PER,COL,BRA
undata mcp-config # print an MCP client config snippet
undata --version
undata serve # start the MCP server (= undata-mcp)Global flags on every data command: --format table|json|csv|parquet (default table) and
--output/-o FILE. Reference commands take --raw for plain-text (AI/pipeline) output.
MCP usage
Point your MCP client at the undata-mcp command. Example (.antigravity.json, already included):
{
"mcpServers": {
"undata": {
"command": "uv",
"args": ["--directory", "C:\\Users\\USER\\source\\MCPs\\UNdata-mcp", "run", "undata-mcp"]
}
}
}undata-mcp and undata serve are equivalent.
Tool | Description |
| List available datasets |
| World Development Indicators for a country |
| Latest snapshot across all WDI indicators |
| Find series codes by keyword |
| Millennium Development Goals data |
| Compare WDI indicators across countries |
| Generic SDMX query for any dataflow |
Architecture
The logic lives in a shared service layer; the CLI and the MCP tools are thin adapters over it, so there is zero duplication between the two interfaces.
services/ core async logic (get_wdi_data, compare_countries, …) ← single source of truth
↑ ↑
tools/ cli/ thin adapters (MCP tools / Typer commands)
registry.py declarative DataflowSpec + build_key() — add datasets by config
cache.py pluggable CacheBackend: MemoryCache (server) / DiskCache (CLI)
client.py async httpx client, cache injected
formatters.py pure CSV → dict shapingAdding a new dataset = one DataflowSpec entry in registry.py (and, if its output shape differs,
one small service function). New interfaces (REST API, notebooks) can reuse services/ unchanged.
Configuration
Copy .env.example to .env (all optional):
UNDATA_CACHE_TTL=600 # response cache seconds (0 = disabled)
UNDATA_TIMEOUT=60 # HTTP timeout seconds (SDMX can be slow)
UNDATA_CACHE_BACKEND=memory # memory | disk (CLI forces disk automatically)
UNDATA_CACHE_DIR=... # override the disk cache locationTests
uv run pytest tests/ -vThis server cannot be installed
Maintenance
Resources
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