ConceptNet MCP Server

Find concepts semantically related to a given concept using ConceptNet's embeddings. This tool uses ConceptNet's semantic similarity algorithms to discover concepts that are related to the input term. Results are ranked by similarity score and include comprehensive analysis. Features: - Semantic similarity discovery using advanced algorithms - Ranked results with detailed similarity analysis - Default English language filtering (can be disabled or changed) - Statistical analysis and categorization - Format control: minimal (~96% smaller) vs verbose (full metadata) Format Options: - verbose=false (default): Returns minimal format optimized for LLM consumption - verbose=true: Returns comprehensive format with full ConceptNet metadata - Backward compatibility maintained with existing tools Similarity Analysis: - Similarity scores from 0.0 (unrelated) to 1.0 (very similar) - Descriptive categories (very strong, strong, moderate, weak, very weak) - Relationship context and likely connections - Language distribution and statistical summaries Use this when you need to: - Discover semantically similar concepts - Expand concept exploration and brainstorming - Find related terms and ideas - Understand semantic neighborhoods

{ "properties": { "filter_language": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": "en", "title": "Filter Language" }, "language": { "default": "en", "title": "Language", "type": "string" }, "limit": { "default": 100, "title": "Limit", "type": "integer" }, "term": { "title": "Term", "type": "string" }, "verbose": { "default": false, "title": "Verbose", "type": "boolean" } }, "required": [ "term" ], "type": "object" }