UNICEF Stats MCP

Name: UNICEF Stats MCP
Author: jpazvd

by jpazvdversion 1.5.5i★ –iRuns on your computer

Registry nameio.github.jpazvd/unicefstats-mcp

Install

Overview

Description from the maker (original English)

UNICEF child development statistics: 790+ indicators, 200+ countries, SDMX-sourced. No API key.

PopNx MCP’s three pillars

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

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiVery new↓ 39/wk · ★ –

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: Databases & datasets

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

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

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": {
    "unicefstats": {
      "command": "uvx",
      "args": [
        "unicefstats-mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add unicefstats -- uvx unicefstats-mcp

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "unicefstats": {
      "command": "uvx",
      "args": [
        "unicefstats-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": {
    "unicefstats": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "unicefstats-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 9, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account jpazvd, 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 Databases & datasetsi

More stars than 0% of the other 1151 servers in this category
Published to the registry more recently than 14% of the other 1151 servers in this category
Basic checks equal to or better than 100% of the other 1151 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 UNICEF Stats 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 (1.5.5) reached the registry 5 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Supabase, MongoDB MCP Server, Elasticsearch MCP Server

Alternatives

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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.

unicefstats-mcp

Experimental — not an official UNICEF product. Verify retrieved values against the UNICEF Data Warehouse before citing in publications. See Limitations.

MCP server for UNICEF child development statistics. Query 790+ child-focused indicators across 200+ countries with disaggregations by sex, age, wealth quintile, and residence. No API key required.

Indicators cover child mortality, nutrition, education, child protection, WASH (water/sanitation/hygiene), HIV/AIDS, immunization, early childhood development, and more. Many align with SDG targets, but the dataset is broader than SDGs alone.

Data source: UNICEF SDMX API

Identity

Property	Value
MCP identity	`io.github.jpazvd/unicefstats-mcp`
PyPI package	`unicefstats-mcp`
Canonical source	github.com/jpazvd/unicefstats-mcp
Data source	UNICEF Data Warehouse via SDMX REST API
Maintainer	Joao Pedro Azevedo (`jpazvd`)
Status	Experimental — not endorsed by UNICEF

Third-party aggregator listings (LobeHub, Smithery, mcp.so, Glama) are not controlled by the maintainer. Verify against the canonical source above.

How it relates to the unicefdata packages
How it compares to other data MCPs
Landscape: MCP servers for official statistics
Relationship to sdmx-mcp
Quick Start
Tools
Demo
Prompts
Benchmark Results
Deployment
Development
Contributing
Limitations and Hallucination Risks
Provenance and Ownership
How to Verify This MCP
License

Key documents

Document	Description
PROVENANCE.md	Data origin, ownership, distribution pipeline, verification steps
CHANGELOG.md	Version history (v0.1.0–v1.5.5) with sources cited
RELEASE.md	Release process checklist and version management
CONTRIBUTING.md	Development setup, code style, PR guidelines
CODE_OF_CONDUCT.md	Contributor Covenant v2.1
examples/RESULTS.md	Full 300-query benchmark analysis with EQA decomposition
examples/LITERATURE_REVIEW.md	Literature review: MCP servers for official statistics — ecosystem, patterns, evaluation, 15 papers
examples/LANDSCAPE.md	Landscape analysis: 20 servers reviewed in depth (March 2026), 92 catalogued with status labels (October 2026) — timeline, feature matrix, strengths/weaknesses
examples/results/related_work.md	Annotated bibliography — 15 papers on tool-augmented hallucination
examples/results/statistical_summary.md	Wilcoxon, bootstrap CI, McNemar tests on benchmark results
examples/MCP-DIRECTORY-STATS.md	Comprehensive directory of all official statistics MCP servers
examples/mcp-smoke-test/MULTIMODEL_SMOKETEST.md	Cross-model smoke test (Anthropic / OpenAI / Google / OpenRouter) for the v0.7.3 cross-provider generalisation question — design, rubric, ~$1 default run, path to full mini-EQA

How it relates to the unicefdata packages

unicefstats-mcp is not a replacement for the unicefdata packages in Python, R, or Stata. They serve different audiences:

	unicefstats-mcp	unicefdata (Python/R/Stata)
Audience	AI assistants (Claude, Cursor, Copilot)	Data scientists, researchers, analysts
Interface	MCP protocol (tool calls via JSON)	Native language API (`library()`, `import`, `ssc install`)
Use case	Conversational data exploration, quick lookups, AI-assisted analysis	Reproducible research, ETL pipelines, statistical analysis
Output	JSON (compact or full) optimized for LLM context	DataFrames, tibbles, Stata matrices
Scripting	No — single queries via AI chat	Yes — full programmatic control, loops, joins, transforms
Caching	Delegates to unicefdata	Built-in SDMX response caching
Bulk download	Limited (max 500 rows per call)	Unlimited — designed for full dataset pulls

Under the hood, unicefstats-mcp wraps the unicefdata Python package. Every tool call ultimately calls unicefdata.unicefData() or its metadata functions. Think of the MCP as a thin AI-friendly interface on top of the same data layer.

When to use which:

Use unicefstats-mcp when you're chatting with an AI and want to quickly explore indicators, check values, or compare countries
Use unicefdata (Python/R/Stata) when you're writing scripts, building dashboards, running regressions, or doing any reproducible analytical work

How it compares to other data MCPs

Servers are named by repository and carry a status label (official, independent, community or commercial) as defined in Status labels. "—" means the feature is not documented in that repository's public README. See About these tables for how counts are taken and how to propose a correction.

Feature	unicefstats-mcp (this repo)	data360-mcp (World Bank, official)	fred-mcp-server (community)	world_bank_mcp_server (community)
Tools	9 (search → metadata → data → code → identity + strict canonical lookup)	16 (search indicators/datasets → metadata → data → disaggregation → codelist lookup → list; summarize / rank / compare countries; country-group expansion; single- and multi-indicator Vega-Lite viz specs; API-URL; plus an interactive-choice UI tool)	3 (browse → search → get)	1 (get only)
Indicators	790+ child-focused indicators	Data360 catalogue, multiple databases (WB_WDI, WB_SSGD, …)	800,000+ economic series	~1,600 indicators
Countries	200+ (ISO3)	200+ (ISO3 `REF_AREA`)	US-focused (some intl)	200+ (ISO2)
Disaggregations	Sex, age, wealth quintile, residence	Sex, age, urbanisation (per indicator, via `data360_get_disaggregation`)	Frequency, seasonal adjustment	None
MCP Prompts	5 (`compare_indicators`, `trend_analysis`, `country_profile`, `sdg_progress`, `write_unicefdata_code`)	7	None	None
MCP Resources	6 (`system-prompt`, `context`, `llm-instructions`, `categories`, `countries`, `glossary`)	11 (`system-prompt`, `context`, `agent-recipe`, `databases`, `codelists`, `data-schema`, `data-filters`, `metadata-fields`, `search-usage`, `viz/chart-grammar`, …)	None	None
Output modes	Compact (5 cols) / Full (all cols)	SDMX-shaped JSON with a per-observation `claim_id` (8-char "proof-carrying numbers" hash); compact serializer for aggregation tools	JSON	CSV
Data summary	Value range, year range, country count	`summarize_data`, `rank_countries`, `compare_countries` tools; Vega-Lite chart specs	None	None
Pagination metadata	`total_rows_available` vs `rows_returned`	`limit`/`offset` with `total_count`, `has_more`, `next_offset` (MCP best-practice pattern)	`limit`/`offset`	None (hardcoded 20K)
Input validation	ISO3, sex, wealth, residence validated	Codelist resolution tool + server-side country-coverage check (`required_country`)	Zod schemas	None
Error guidance	`error` + `tip` with next steps	Structured `error_code` (e.g. `http_error:search`) + message, raised as MCP `ToolError`	HTTP status text	Raw exception
API key	Not required	Not required	FRED_API_KEY required	Not required
Truncation handling	`rows_truncated` flag + filter tips	Payload stripping to core fields with `claim_id` preserved (`docs/payload_analysis.md`)	None	None
Published	PyPI	PyPI	npm	No

Landscape: MCP servers for official statistics

This project is part of a growing ecosystem of MCP servers for international and official statistics. Tables group servers by the data source they wrap; the Status column says who maintains them, using the labels defined in Status labels.

About these tables

Status labels

Status describes who maintains a server, not its quality or the quality of its data.

Official: published by the organisation that produces the data, or that operates the platform it is served from, under that organisation's account or announced on its own website. A qualifier marks maturity where the organisation states it: *(beta)*, *(lab)*, *(pilot)*.
Independent: built by staff of that organisation in a personal capacity, as stated in the README or the maintainer's profile, and not endorsed by the organisation. This repository is in this category.
Community: built by individuals or groups with no stated affiliation to the data producer.
Commercial: offered by a company as part of a product or a hosted or paid service, with no stated affiliation to the data producer.

*Official* refers to the server, not the data. Servers whose data are not official statistics, such as research estimates, are listed separately in the directory; a research producer that maintains its own server is labelled *producer-maintained*, not official.

When the evidence is ambiguous, we do not claim official or independent status: the row is labelled community and the note says why. Affiliations we cannot see can be added through the landscape-correction issue template below.

Counts and corrections

The comparison and landscape tables are a snapshot, not a registry. Every count (tools, prompts, resources, stars) describes what is visible on each repository's public default branch on the date of the commit that last touched the row — currently 2026-10-24 to 2026-10-27 — and the ecosystem moves faster than this README. The

Only the beginning is shown; read the rest in the repo

UNICEF Stats MCP

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Databases & datasetsi

Common questions

Alternatives

Supabase

MongoDB MCP Server

Elasticsearch MCP Server

README from the maker

unicefstats-mcp

Identity

Contents

Key documents

How it relates to the unicefdata packages

How it compares to other data MCPs

Landscape: MCP servers for official statistics

About these tables

Status labels

Counts and corrections