Semantic Search
Industry Definition Set • Entity Resolution Path: /glossary/semantic-search
Quick Answer / TL;DR
A search technique that uses embedding similarity to find documents relevant to a query's meaning, rather than relying solely on keyword matching.
Key Takeaways
- Finds documents by meaning, not just keywords.
- Uses embedding vectors and similarity metrics.
- Captures synonyms and conceptual relationships.
- Core retrieval mechanism in MCP RAG systems.
Definitive Statement: A search technique that uses embedding similarity to find documents relevant to a query's meaning, rather than relying solely on keyword matching.
Technical Context & Protocol Usage
- Detailed Explanation
- Semantic search converts both the query and documents into embedding vectors, then finds the nearest neighbors to the query vector. This captures synonyms, paraphrases, and conceptual relationships that keyword search misses. In MCP RAG servers, semantic search is the primary retrieval mechanism for finding relevant context for the LLM.
Format & Payload Metadata
Format: Embedding vectors + cosine similarity or other distance metrics
Latency: 50-200ms per query for typical index sizes
Real-World Implementation Use Case
An MCP RAG server uses semantic search to find documents about 'employee leave policy' even when the query uses synonyms like 'vacation days'.
Cite This Page
MLA Style:
MCPserver.in Engineering. "Semantic Search." MCPserver.in Knowledge Hub, 20 July 2026, mcpserver.in/glossary/semantic-search.
Related Terms
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A local-only transport mechanism where the AI client spawns the MCP server as a child process and communicates via standard input (stdin) and standard output (stdout) channels.
SSE Transport (Server-Sent Events)
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