Baidu Search MCP Server

The Baidu Search MCP Server equips AI assistants with a reliable, high‑performance web search capability that leverages Baidu’s extensive index while respecting local rate limits. By exposing a concise tool, the server allows developers to embed real‑time search results directly into conversational flows or knowledge‑base queries, bridging the gap between static LLM knowledge and dynamic internet content. For teams building Chinese‑language assistants or applications that require up‑to‑date information, this server removes the need to manage complex scraping pipelines or third‑party APIs.

At its core, the server offers two primary tools: search and fetch_content. The search tool performs a Baidu query, applies intelligent filtering to strip out ads and redirect wrappers, and formats the top results into a clean, LLM‑friendly string. The content fetching tool retrieves a webpage, parses the DOM to extract meaningful text, and returns it in a concise format suitable for downstream processing. Both tools include built‑in rate limiting (30 requests per minute for search, 20 for fetching) and a queueing mechanism that automatically pauses when limits are reached, ensuring compliance with Baidu’s usage policies without manual intervention.

Developers can integrate the server into their AI workflows by adding it to a Claude Desktop configuration or any MCP‑compatible client. Once registered, the assistant can invoke to surface up‑to‑date answers or call to pull in detailed articles, news stories, or product pages. The server’s output is deliberately structured for language models: titles, URLs, and snippets are clearly delineated, while fetched content is trimmed to avoid overwhelming the model with noise. This design choice improves response quality and reduces hallucination risk when the assistant references external sources.

Unique advantages of this MCP server include its LLM‑friendly output formatting, which eliminates the need for additional parsing logic in client code, and its robust error handling—every failure is logged through the MCP context and reported back to the assistant, enabling graceful degradation or fallback strategies. The server also supports future extensibility: contributors can add regional search parameters, caching layers for frequent queries, or alternative content extraction heuristics without altering the client interface.

In real‑world scenarios, teams building customer support bots for Chinese markets can use this server to fetch the latest policy updates or product specifications. Research assistants can quickly pull in recent academic articles from Chinese journals, while e‑commerce platforms might surface live reviews or price comparisons. By abstracting the intricacies of Baidu’s search engine and web scraping, the Baidu Search MCP Server empowers developers to focus on higher‑level conversational logic while maintaining access to fresh, authoritative information.