AQICN Air Quality
This MCP server, developed by mattmarcin, provides integration with the World Air Quality Index (AQICN) API for retrieving real-time air quality data. Built with Python and leveraging libraries like FastMCP and Pydantic, it offers tools for querying air quality information by city name or coordinates, as well as searching for monitoring stations. The implementation focuses on providing a standardized interface for accessing global air quality metrics, enabling AI assistants to incorporate up-to-date environmental data into their responses. It's particularly useful for applications in environmental monitoring, public health, and urban planning, allowing for easy integration of air quality considerations into AI-driven decision-making processes without requiring direct interaction with the AQICN API.
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
- monitoring
- Source
- PulseMCP
- Repository
- github.com/mattmarcin/aqicn-mcp
- Author type
- human
- Updated
- 2026-04-25
Use via MCP
Resolve AQICN 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.