"A source for finding weather information" matching MCP servers:

Enables mapping JavaScript error stack traces back to original source code, extracting context information to help developers locate and fix issues.

Analyzes source code dependencies across multiple programming languages in the specified directory to identify file relationships, assisting in dependency management and project structure understanding.

An MCP server that enables AI assistants to navigate, search, and analyze local Keycloak source code to support developer customizations like SPIs and authenticators. It provides tools for searching classes, generating boilerplate code, detecting breaking changes between versions, and tracing dependencies.

Multi-datasource MCP server that connects AI assistants to 6 database types (MySQL, PostgreSQL, ClickHouse, MongoDB, SQLite, Huawei DWS) with dynamic configuration, encrypted credential storage, and schema discovery.

Indexes Unreal Engine source code into a local database, providing AI coding assistants with deep structural queries like class hierarchies, call graphs, and full-text search across all engine source files.

Enables users and AI tools to query synchronized AOSP and AndroidX source code on demand for precise inspection of Android framework internals and Jetpack libraries. Supports class and method lookup, class member listing, inheritance hierarchy, source search, and optional cross-file definition, reference, and type information via LSP.

Provides AI tools with on-demand, precise access to real AOSP framework and AndroidX source code, so they can search classes, extract exact method bodies with Javadoc, inspect inheritance hierarchies, and trace definitions and references across the entire tree. Sources are synced locally for fast, offline lookups, with optional language-server features for cross-file navigation.

Enables on-demand, precise access to AOSP and AndroidX source code, allowing AI tools to inspect framework internals, search classes and methods, trace inheritance and references, and retrieve type information from a locally synced cache.

Provides AI tools with on-demand, precise access to AOSP and AndroidX source code for methods, classes, members, inheritance, definitions, references, and type information. It supports local source syncing/updating and optional LSP-powered cross-file navigation.

A Model Context Protocol (MCP) server built with the mcp-framework to provide weather-related tools and data to AI clients. It enables integration of weather capabilities and custom tools into the MCP ecosystem for use with platforms like Claude Desktop.

Enables AI tools to retrieve and navigate actual AOSP and AndroidX source code on demand for accurate framework internals, with tools for class/method lookup, member listing, hierarchy, and source search. Optional LSP features add cross-file definitions, references, and type information.

Odds are, most of what you want to build is already open source. Tell your AI agent what you're making, and it finds it: which repos to use as they are, which to adapt, and what's left for you to write. Every repo it names is real, licensed for your use or flagged, and checked live.

A step-by-step workshop for building an MCP server that provides weather tools to AI agents, enabling secure API key usage.

Enables coding agents to add a bounded semantic-judgment layer for routing, ranking, extraction, verification, and escalation, returning typed signals and review recommendations.

Serves Open-Meteo weather forecasts from a standalone stdio MCP process, letting any MCP client fetch forecast data without importing the harness into the plugin process. It pairs this with a comparison suite that measures in-process plugin behavior against the signed MCP bridge, documenting isolation and trust-ladder evidence.

Provides on-demand access to AOSP and Jetpack source code to help AI understand Android framework internals. It features a hybrid architecture using Tree-sitter and LSP for precise code extraction, cross-file navigation, and local source indexing.

A simple service using Model Context Protocol (MCP) to provide weather information for multiple cities including Fukuoka, Tokyo, Osaka, Moscow, and New York.

Provides over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Provides AI assistants with on-demand, precise access to real AOSP and AndroidX source code, enabling class and method lookups, class member and hierarchy inspection, source-wide text/regex search, and optional cross-file definition, reference, and type resolution via LSP. Sources are synced locally for instant offline queries against framework internals like the Activity lifecycle, ViewModel restoration, and Compose internals.