UNHCR Open Data Gateway MCP
Provides a unified interface to access UNHCR's open data across statistics, RDF, and IATI MCP servers, enabling aggregated queries, cross-domain analytics, and dataset discovery.
README
UNHCR Open Data Gateway MCP
A FastMCP-based gateway that aggregates and normalizes data from UNHCR's domain-specific MCP servers.
🎯 Purpose
The UNHCR Open Data Gateway MCP provides a unified interface for accessing UNHCR's open data across three independent MCP servers:
- Statistics MCP: Authoritative source for population and displacement data
- RDF MCP: Authoritative source for socio-economic indicators and contextual datasets
- IATI MCP: Authoritative source for budget, contributions, and financial transparency data
🏗️ Architecture
The gateway follows a Federated Gateway Pattern:
AI Client
|
v
+----------------------+
| Open Data Gateway |
| FastMCP |
+----------------------+
/ | \
/ | \
v v v
+---------+ +---------+ +---------+
| Stat | | RDF | | IATI |
| MCP | | MCP | | MCP |
+---------+ +---------+ +---------+
^
|
|
Reference Layer
(Canonical Entities)
Core Principles
- Domain MCP Ownership: Each domain MCP owns its data
- Gateway Owns Experience: Gateway handles aggregation, composition, discovery, analytics
- Domain MCP Independence: Domain MCPs never call each other directly
- Canonical Reference Layer: Prevents duplication of country/operation definitions
🚀 Quick Start
Installation
# Clone the repository
git clone <repository-url>
cd unhcr-opendata-gateway-mcp
# Create virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install dependencies
pip install -r requirements.txt
Configuration
Create a .env file:
STAT_MCP_ENDPOINT=http://localhost:8001
RDF_MCP_ENDPOINT=http://localhost:8002
IATI_MCP_ENDPOINT=http://localhost:8003
LOG_LEVEL=INFO
Running the Server
# Run in STDIO mode
python -m src.unhcr_opendata_gateway.app
🛠️ Usage
Available Tools
| Tool | Description | Parameters |
|---|---|---|
country_snapshot |
Comprehensive snapshot for a country | country, year |
operation_snapshot |
Comprehensive snapshot for an operation | operation, year |
funding_gap_analysis |
Calculate funding gap and per-refugee metrics | country, year |
funding_per_refugee |
Calculate funding metrics per refugee | country, year |
compare_countries |
Compare two countries across all domains | country_a, country_b, year |
search_datasets |
Search datasets across all MCPs | query, country, region, topic, dataset |
list_all_datasets |
List all available datasets | - |
generate_country_brief |
Generate a comprehensive briefing note | country, year |
Example Queries
# Get a country snapshot
result = await country_snapshot(country="Uganda", year=2023)
# Calculate funding gap
result = await funding_gap_analysis(country="Chad", year=2023)
# Compare two countries
result = await compare_countries(country_a="Uganda", country_b="Kenya", year=2023)
# Generate a briefing note
result = await generate_country_brief(country="Sudan", year=2023)
📊 Features
- Country Normalization: Handles ISO3, ISO2, names, aliases, "Republic of X" variants
- Cross-Domain Analytics: Funding gap per refugee, budget per refugee, etc.
- Graceful Degradation: Returns partial data when some MCPs are unavailable
- Caching: TTL-based caching with configurable expiration
- Observability: Structured logging, metrics, OpenTelemetry tracing
📄 License
Apache License 2.0
🙏 Support
For issues or questions, please contact the UNHCR Data team.
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