modelscope·@BochaAI/bocha-search-mcp
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v1
Bocha is a search engine for AI, enabling your AI applications to access high-quality world knowledge from nearly 10 billion web pages and content sources, covering various fields such as weather, news, encyclopedia, healthcare, train tickets, and images.
Bocha is a search engine for AI, enabling your AI applications to access high-quality world knowledge from nearly 10 billion web pages and content sources, covering various fields such as weather, news, encyclopedia, healthcare, train tickets, and images.
Web Search
Search, News, Weather, Encyclopedia
Search the entire web and web links via Bocha, returning results that include web page titles, URLs, summaries, website names, website icons, publication dates, and image links.
Input:
Output:
Building on Bocha's web search, AI identifies the semantics of the search terms and additionally returns structured modal cards for specific verticals, such as weather cards, calendar cards, and encyclopedia cards, among dozens of others. This provides better performance in semantic recognition, timeliness of search results, and richness of content.
Input:
Output:
Ark, Python, Claude, Cursor, etc.
You need to visit the Bocha AI Open Platform, log in, and obtain an API KEY.
API Key
bash git clone git@github.com:BochaAI/bocha-search-mcp.git
On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
json "mcpServers": { "bocha-search-mcp": { "command": "uv", "args": [ "--directory", "/path/to/bocha-search-mcp", "run", "bocha-search-mcp" ], "env": { "BOCHA_API_KEY": "sk-****" } } }

bash npx @modelcontextprotocol/inspector uv --directory /path/to/bocha-search-mcp run bocha-search-mcp
Bocha has served over 3,000 enterprise users and 20,000 developer users, becoming the official networked search provider for DeepSeek and the recommended search API by Alibaba, Tencent, and ByteDance. Currently, it handles over 60% of the networked search requests for AI applications in China.
The content sources for Bocha's search include nearly 10 billion web pages and ecosystem partner content (including short videos, news, encyclopedias, weather, healthcare, train tickets, hotels, restaurants, attractions, businesses, and academic resources). Bocha will continue to collaborate with various platforms on content ecosystems and intelligent agent creation, providing rich and diverse answers to search queries for its users.
Traditional search engines use a keyword + bid ranking mechanism in their search algorithms. The goal of the search results is not to directly provide the correct answers to users but to attract user clicks to generate advertising revenue.
Bocha is a next-generation search engine based on multimodal hybrid search and semantic ranking technology. It supports natural language search methods for AI application scenarios, and the objective of the search results is to provide clean, accurate, and high-quality answers.
Bocha's semantic ranking technology is based on the Transformer architecture, which ranks search results according to their semantic relevance to the user's query. Since large models also use the Transformer architecture and make decisions based on the semantic relevance between context and user queries, these large models tend to prefer the search results provided by Bocha.
Currently, Bocha's search performance is the closest to that of the Bing Search API among domestic search engines. Because the Bing Search API data is hosted overseas (no domestic region), is expensive (15 USD per thousand requests), and does not provide text summaries (only 50-100 character snippets), many domestic enterprise customers have switched from Bing to Bocha.
Bocha AI Search, built on top of Bocha Web Search, uses AI to recognize the semantics of search terms and returns additional structured mo…
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