Cito
Hybrid academic search over 236M papers, built for agents
About Cito
Cito is a cutting-edge hybrid academic search engine designed for researchers, developers, and AI agents. It combines a vast corpus of 236 million papers from Semantic Scholar with advanced vector search capabilities using SPECTER2 dense embeddings, integrated with re-ranking techniques like Reciprocal Rank Fusion (RRF) and cross-encoder reranking for highly relevant results. Its primary appeal lies in enabling deep literature research through a free web interface, a straightforward JSON API, and a dedicated MCP endpoint that supports powerful AI agents such as Claude Code without upstream rate limits. Built to overcome the throttling limitations of traditional academic APIs, Cito empowers users to perform rapid, large-scale scholarly searches with precision and speed. Its seamless integration and open accessibility make it ideal for developers, academic researchers, and AI-driven applications seeking reliable, high-volume academic data retrieval.
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Pros
- ✓Extensive corpus of 236 million academic papers for comprehensive searches
- ✓Hybrid search combining keyword, dense vector, and reranking methods for high relevance
- ✓No signup required for web search, with a simple API and MCP endpoint for integration
- ✓Designed to support AI agents with minimal rate limiting
- ✓Free access, enabling wide adoption and experimentation
Cons
- ✗Limited information on advanced filtering or customization options
- ✗No details on premium features or tiered pricing if available
- ✗Potential complexity for non-technical users to fully leverage API integrations
Use Cases
Pricing
Likely offers a free tier with open access to its search engine and API, possibly with usage limits. Premium plans or enterprise options are not specified but could be available for higher volume or advanced features.
Quick Info
Topics
Makers
Tao An
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