pangerl-mcp-server-weather
An MCP server (weather) that likely exposes weather-related tools/data to AI agents via the Model Context Protocol. The repository name suggests it wraps a weather provider API and offers agent-invokable functions, but no manifest/README contents were provided here to confirm exact tools, parameters, endpoints, or provider used.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
No repository details were provided, so scores are based on typical risks for MCP wrappers around third-party APIs. Key security concerns to verify: TLS usage, how API keys are loaded/stored, whether logs redact secrets, and dependency/vulnerability posture.
⚡ Reliability
Use Cases
- • Agent can fetch current weather/forecasts for a location
- • Automated weather lookups for scheduling, travel planning, or context enrichment
- • Building agent workflows that react to weather conditions
Not For
- • Security-sensitive production workloads without verifying auth, logging, and dependency posture
- • Use as a substitute for a fully vetted weather API integration where accuracy, SLAs, and licensing are contractually clear
- • High-throughput or latency-critical systems if rate limits/timeouts aren’t documented and handled
Interface
Authentication
No authentication details were provided in the prompt. MCP servers commonly use environment variables/API keys for upstream weather providers, but this is not verifiable from the given information.
Pricing
Pricing information not provided. If it proxies a third-party weather API, costs may depend on that provider’s billing/rate limits.
Agent Metadata
Known Gotchas
- ⚠ Weather lookups may require a location format (city name vs lat/long) that agents can mis-specify
- ⚠ If the MCP tool triggers upstream API calls, agents may need guidance on retries/backoff when rate-limited
- ⚠ Some weather APIs treat city names ambiguously (time zone/locale issues)
Alternatives
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Scores are editorial opinions as of 2026-04-04.