Weather
This weather service MCP server, developed for integrating weather data into AI assistants, provides a streamlined interface for accessing real-time weather information. It utilizes the httpx library for efficient HTTP requests and integrates with external weather APIs to fetch current conditions, forecasts, and other meteorological data. The server's modular structure, defined in the pyproject.toml, allows for easy deployment and scalability. By connecting AI capabilities with weather data, this implementation enables assistants to provide location-specific weather updates, plan outdoor activities, or analyze climate patterns. It is particularly useful for applications requiring up-to-date weather information, travel planning, or any scenario where an AI system needs to reason about and respond to current and forecasted weather conditions.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-28.
Scan details: Circle-IR · 2026-09-28 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- devops-ci
- Source
- PulseMCP
- Author type
- human
- Last scanned
- 2026-09-28
- Updated
- 2026-09-28
Use via MCP
Resolve Weather 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.