Lesson 1: MCP Primer
Topics Covered
- What embeddings are and how they represent meaning as vectors.
- Why vector size (dimensionality) matters for accuracy, memory, and speed.
- Differences between cosine similarity, dot product, and Euclidean distance.
- Using
SentenceTransformersto generate and compare embeddings in Python.