About
A Model Context Protocol server that fetches up-to-date information from the web using pluggable search providers, currently integrated with Brave Search API. It returns structured JSON results and categorizes queries for context-aware AI responses.
Capabilities

Overview
The MCP Web Search Tool is a Model Context Protocol server that grants AI assistants instant access to fresh, real‑time information from the web. By exposing a single tool that queries an external search provider, developers can empower conversational agents with up‑to‑date facts about weather, sports scores, stock markets, and breaking news—capabilities that static knowledge bases simply cannot provide. This addresses a core limitation of many AI assistants: the inability to browse the internet on demand while maintaining consistent, structured responses.
At its core, the server acts as a thin adapter between the MCP framework and a search API. The current implementation plugs into the Brave Search API, but its pluggable architecture allows developers to swap in Google, Bing, or any custom provider with minimal changes. The server accepts a search term and optional provider flag, forwards the query to the chosen API, then normalizes the response into a clean JSON format. This standardization simplifies downstream processing for AI agents, which can parse results without handling provider‑specific quirks.
Key capabilities include automatic query categorization and context‑aware guidance. The tool distinguishes between weather, news, sports, finance, or general queries and tailors the response accordingly. This ensures that agents receive concise, relevant data—such as a current temperature or the latest stock ticker—without extraneous noise. The structured output also supports advanced features like result ranking, relevance scoring, and pagination through the configuration.
Developers can integrate this server into a wide range of workflows. In the Claude Desktop ecosystem, for example, the tool can be registered as an MCP server and invoked whenever a user asks a time‑sensitive question. The agent then automatically triggers the web search, retrieves fresh data, and crafts a response that feels instantaneous. Beyond desktop assistants, any application that relies on MCP—such as chatbots in customer support or data‑driven dashboards—can leverage the same server to keep information current without building custom web‑scraping logic.
What sets this MCP Web Search Tool apart is its balance of simplicity and extensibility. It requires only a single API key, exposes a minimal set of parameters, yet delivers a robust interface for real‑time data retrieval. The modular provider design encourages experimentation and future upgrades, while the structured JSON output ensures compatibility with existing MCP clients. For developers looking to give their AI assistants a reliable, up‑to‑date knowledge source, this server provides a plug‑and‑play solution that scales from small prototypes to production deployments.
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