Baidu Search MCP Server

Created By
Evilrana year ago
Baidu Search MCP Server I A Model Context Protocol (MCP) server that provides web search capabilities through Baidu, with additional features for content fetching and parsing.
Overview

What is Baidu Search MCP Server?

Baidu Search MCP Server is a Model Context Protocol (MCP) server that provides web search capabilities through Baidu, along with features for content fetching and parsing.

How to use Baidu Search MCP Server?

To use the server, install it via Smithery or directly from PyPI, and configure it with Claude Desktop to enable web search and content fetching functionalities.

Key features of Baidu Search MCP Server?

  • Web Search: Advanced search capabilities with result formatting.
  • Content Fetching: Intelligent retrieval and parsing of webpage content.
  • Rate Limiting: Protection against exceeding request limits.
  • Error Handling: Comprehensive logging and error management.
  • LLM-Friendly Output: Results formatted for large language model consumption.

Use cases of Baidu Search MCP Server?

  1. Performing web searches on Baidu with formatted results.
  2. Fetching and parsing content from various web pages.
  3. Integrating with applications that require web search functionalities.

FAQ from Baidu Search MCP Server?

  • Can I use this server for any web search?

Yes, it is designed to perform searches specifically on Baidu.

  • Is there a limit to the number of requests?

Yes, the server has built-in rate limiting to manage requests effectively.

  • How can I contribute to the project?

You can submit issues and pull requests on the GitHub repository.

Project Info
Created At
a year ago
Updated At
a year ago
Author Name
Evilran
Star
1
Language
Python
License
MIT license

Recommend Servers

View All
//beforeyouship — LLM Cost Modeling From Your Editor
@Indiegoing

Query realistic LLM cost models without leaving your editor. beforeyouship models the **true monthly cost** of an LLM app architecture — retries, prompt caching, batch discounts, infra overhead, and 3×/10× growth — across GPT-5.x, Claude, Gemini, DeepSeek, and more. Not a token calculator: a planning tool for the design phase, before you commit to a stack. **No API key needed to try it** — demo mode covers the six free-tier models. A Pro key from [beforeyouship.dev](https://beforeyouship.dev) unlocks the full 18-model catalog. ## What you can ask - "How much will a RAG chatbot cost at 10,000 requests/day?" - "Compare Claude Haiku vs Gemini Flash pricing for my workload" - "What's the cheapest model for a multi-step agent at scale?" - "Show me current per-token prices for Anthropic models" ## Tools ### `estimate_cost` Full cost model for an architecture at a given usage level. Returns Naive / Realistic / Worst Case monthly cost per model, 3×/10× growth scenarios, and an opinionated recommendation with reasoning. ### `get_model_prices` Current per-1M-token pricing — input, output, cached input, batch — with context windows and staleness metadata. ### `list_archetypes` Seven preset architecture patterns (simple chatbot, chatbot with history, RAG pipeline, multi-model router, coding assistant, document processor, multi-step agent) used as starting points for estimates. ## Setup **Claude Code:** ​```bash claude mcp add --transport http beforeyouship https://beforeyouship.dev/api/mcp ​``` **Cursor / other clients** — add a remote server: ​```json { "mcpServers": { "beforeyouship": { "type": "streamable-http", "url": "https://beforeyouship.dev/api/mcp" } } } ​``` Add an `Authorization: Bearer bys_...` header with a Pro key for the full catalog. ## Try it > Estimate the monthly cost of a RAG pipeline at 10,000 requests/day

13 hours ago
Shippo
@Shippo

21 hours ago