ConceptNet
Provides structured access to the ConceptNet knowledge graph, delivering semantic knowledge for Large Language Models and AI applications.
About
Leveraging the FastMCP framework, ConceptNet offers AI assistants and applications structured access to ConceptNet's vast semantic knowledge. It provides four powerful tools: Concept Lookup for detailed information, Concept Query for advanced filtering, Related Concepts for semantic connections, and Concept Relatedness for similarity scores. Designed for optimal performance and efficiency, it features comprehensive multi-language search, async operations, type safety, and optimized output formats (minimal or verbose) specifically tailored to reduce token usage and enhance LLM consumption. It also supports seamless deployment to Cloudflare Workers for global, auto-scaling access.
Key Features
- Serverless deployment option via Cloudflare Workers for global, auto-scaling access
- Optimized Output Formats (Minimal/Verbose) for efficient LLM consumption
- 0 GitHub stars
- Multi-language Support for accessing ConceptNet's knowledge base
- Comprehensive Concept Search, Querying, and Relatedness tools
- FastMCP Integration for high-performance ConceptNet access
Use Cases
- Optimizing Large Language Model (LLM) interactions by providing structured, context-rich data
- Enriching AI assistants and applications with real-time semantic knowledge
- Performing advanced concept lookup, querying, and relationship analysis
