Google Air Quality
This MCP server implementation provides AI assistants with comprehensive access to Google's Air Quality API, enabling real-time air quality queries for any location worldwide. Developed by ContexaAI in Go, it offers four primary tools for retrieving current conditions, hourly forecasts, historical measurements, and heatmap tile visualizations across eight regional index types. The server includes LLM-friendly prompts that automatically resolve natural language location names to coordinates, making it easy for AI assistants to answer air quality questions without manual geocoding. It's particularly valuable for environmental monitoring, health-related queries, and location-based air quality analysis.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately.
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- ai-ml
- Source
- PulseMCP
- Repository
- github.com/synqedai/google-air-quality-mcp
- Author type
- human
- Updated
- 2026-04-25
Use via MCP
Resolve Google Air Quality from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.