{"id":"pangerl-mcp-server-weather","name":"pangerl-mcp-server-weather","homepage":"https://pypi.org/project/pangerl-mcp-server-weather/","repo_url":null,"category":"ai-ml","subcategories":[],"tags":["mcp","weather","ai-agents","tooling","integration"],"what_it_does":"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.","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"],"best_when":null,"avoid_when":null,"alternatives":["Direct integration with a weather API (e.g., Open-Meteo, WeatherAPI, OpenWeather) via your own backend","Use an existing MCP/weather tool from a trusted registry, or a general-purpose MCP server with verified tool specs","Implement weather tool using server-side fetch with explicit caching and retry logic"],"af_score":39.2,"security_score":37.8,"reliability_score":17.5,"package_type":"mcp_server","discovery_source":["pypi"],"priority":"low","status":"evaluated","version_evaluated":null,"last_evaluated":"2026-04-04T21:49:18.640796+00:00","interface":{"has_rest_api":false,"has_graphql":false,"has_grpc":false,"has_mcp_server":true,"mcp_server_url":null,"has_sdk":false,"sdk_languages":[],"openapi_spec_url":null,"webhooks":false},"auth":{"methods":["unknown"],"oauth":false,"scopes":false,"notes":"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":{"model":null,"free_tier_exists":false,"free_tier_limits":null,"paid_tiers":[],"requires_credit_card":false,"estimated_workload_costs":null,"notes":"Pricing information not provided. If it proxies a third-party weather API, costs may depend on that provider’s billing/rate limits."},"requirements":{"requires_signup":false,"requires_credit_card":false,"domain_verification":false,"data_residency":[],"compliance":[],"min_contract":null},"agent_readiness":{"af_score":39.2,"security_score":37.8,"reliability_score":17.5,"mcp_server_quality":55.0,"documentation_accuracy":35.0,"error_message_quality":0.0,"error_message_notes":null,"auth_complexity":60.0,"rate_limit_clarity":20.0,"tls_enforcement":40.0,"auth_strength":40.0,"scope_granularity":20.0,"dependency_hygiene":45.0,"secret_handling":45.0,"security_notes":"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.","uptime_documented":0.0,"version_stability":40.0,"breaking_changes_history":0.0,"error_recovery":30.0,"idempotency_support":"false","idempotency_notes":null,"pagination_style":"none","retry_guidance_documented":false,"known_agent_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)"]}}