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dhis2-analytics

Retrieve aggregated DHIS2 analytics data across data elements, indicators, org units, and periods.

Updated Jan 20, 2026
Search Tags:#analytics#queries#indicators#periods#dhis2#data-elements#org-units
One-click install
npx skills add https://github.com/BLSQ/mcp_servers --skill dhis2-analytics
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: dhis2-analytics
Source: https://github.com/BLSQ/mcp_servers/tree/main/.claude/skills/dhis2-analytics
Command: npx skills add https://github.com/BLSQ/mcp_servers --skill dhis2-analytics

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill enables querying and retrieving aggregated analytics data from DHIS2, including calculated values, indicator data, and cross-dimensional insights to support data-driven decision making.

Core Features & Use Cases

  • DHIS2 analytics queries: fetch data elements, indicators, and groups across org units and periods.
  • Aggregated insights: compute sums or other aggregations at specified levels or groupings.
  • Use Case: an analyst runs a report to monitor quarterly indicators across facilities and presents results in a dashboard.

Quick Start

Use the dhis2-analytics skill to fetch aggregated analytics for data elements ["dx1","dx2"] in org unit "OU_01" for periods ["202401"].

Frequently Asked Questions about dhis2-analytics

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I retrieve aggregated DHIS2 analytics data for specific data elements and periods?▼

You retrieve aggregated DHIS2 analytics data by configuring a Python environment with a DHIS2 client library to build and execute analytics requests. This returns structured results for specified data elements, indicators, org units, and periods.

What is cross-dimensional analysis in DHIS2 and how does it support data-driven decisions?▼

Cross-dimensional analysis in DHIS2 involves querying aggregated data across multiple dimensions like data elements, indicators, org units, and periods. It enables both simple queries and combined analyses to produce calculated values and aggregated insights.

Do I need a Python environment to query DHIS2 indicators and org units?▼

Yes, you need a configured Python environment with a DHIS2 client library and standard tooling. This setup allows you to build and execute analytics requests to fetch data elements, indicators, and groups across org units and periods.

Can I compute sums and other aggregations at specified org unit levels in DHIS2?▼

Yes, you can compute sums or other aggregations at specified levels or groupings within DHIS2. The analytics queries support fetching aggregated insights for data elements, indicators, and groups across various org units and periods.

What's the best way to fetch quarterly indicators across multiple facilities in DHIS2?▼

The best way to fetch quarterly indicators across facilities is by using analytics queries that combine data elements, indicators, org units, and periods. An analyst can run these queries to monitor indicators and present results in a dashboard.

Why does my DHIS2 analytics query return empty results for certain periods?▼

Empty results may occur if the specified periods, data elements, or org units do not contain aggregated data. Ensure your analytics requests are correctly configured with valid DHIS2 identifiers for the dimensions you are querying.

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