The MCP Server
for Scientific AI Applications
Get cutting-edge scientific and technological knowledge
context for your AI applications.
Scientific RAG out of the box
Access state-of-the-art knowledge beyond the training set
Enhance RAG applications with real-time information in science and technology.
Inform models with high-quality embeddings and symbolic knowledge
Get embedded or symbolic information about topics across science, technology, and industry.
Set information quality standards
Filter scientific and technological context on measures of quality, impact, target domain, and more.
Topical and trend information
fit to context
fit to context
Compress recent scientific and technological history into AI context
Receive time series of semantic queries, topic growth, method usage, and more across domains.
Expand scope and diversify model predictions
Access semantic and topic growth predictions, topical correlations, and translational predictions.
Populate context from a diversity of entities and sources
Retrieve researchers, inventors, or organizations by their topical expertise across science or industry.
State-of-the-art bibliometrics
to boost signal
to boost signal
Set custom source filters to ensure AI contexts match intuition
Filter for quality of knowledge sources, authorship or organization, and time period relevance.
Monitor emerging impact with historical and predictive bibliometrics
Query trends in citation-based or text-based measures of research and technology impact.
See further into the knowledge frontier with state-of-the-art metrics
Get multiple impact-correlated predictions on the growth of topic areas, semantic queries, and more.