{"name":"Moss","version":"1.0.0","protocolVersion":"1.0.0","description":"Real-time semantic search runtime for AI agents. Sub-10ms semantic, keyword, or hybrid retrieval against project-owned indexes, hosted or on-device. Supports bring-your-own embeddings.","url":"https://www.moss.dev","documentationUrl":"https://docs.moss.dev","provider":{"organization":"InferEdge Inc.","url":"https://www.moss.dev"},"defaultInputModes":["application/json"],"defaultOutputModes":["application/json"],"supportedInterfaces":[{"url":"https://service.usemoss.dev/v1","transport":"HTTP"}],"capabilities":["semantic-search","keyword-search","hybrid-search","vector-indexing","bring-your-own-embeddings"],"skills":[{"id":"semantic-search","name":"Semantic Search","description":"Sub-10ms similarity search against a project index. Tunable alpha blends pure semantic (1.0) and pure keyword/BM25 (0.0) retrieval. Supports top-k, metadata filters, and optional pre-computed query embeddings."},{"id":"index-management","name":"Index Management","description":"Create, load, list, and delete semantic search indexes. Built-in embedding models moss-minilm (fast, default) and moss-mediumlm (higher accuracy), or bring-your-own embeddings per document."},{"id":"document-operations","name":"Document Operations","description":"Add, upsert, retrieve, and delete documents within an index. Documents carry id, text, optional string-keyed metadata for filtering, and optional pre-computed embeddings."}]}