What is the default embedding model?
The default embedding model is `Xenova/all-MiniLM-L6-v2`, configured via the `EMBEDDING_MODEL` environment variable.
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Brain Server - MCP Knowledge Embedding Service is an MCP (Model Context Protocol) server for managing knowledge embeddings and vector search. It integrates with AI applications via the Model Context Protocol and organizes knowledge into domain-specific brains.
Clone the repository, install dependencies (npm install), copy .env.example to .env and configure PORT, MONGODB_URI, EMBEDDING_MODEL, and MAX_CHUNK_SIZE. Build with npm run build, then run in development mode (npm run dev) or production mode (npm start). Use the exposed MCP tools such as addKnowledge, searchSimilar, updateKnowledge, deleteKnowledge, batchAddKnowledge, and getEmbedding.
The default embedding model is `Xenova/all-MiniLM-L6-v2`, configured via the `EMBEDDING_MODEL` environment variable.
The server requires MongoDB, configured through the `MONGODB_URI` environment variable.
Copy `.env.example` to `.env` and set `PORT`, `MONGODB_URI`, `EMBEDDING_MODEL`, and `MAX_CHUNK_SIZE` as needed.
Run `npm run dev` for development mode with hot reloading.
The server exposes `addKnowledge`, `searchSimilar`, `updateKnowledge`, `deleteKnowledge`, `batchAddKnowledge`, and `getEmbedding`.

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