Persistent semantic memory for any AI agent
27 MCP tools. SQLite or Firestore. Pluggable embeddings. Give your agent a mind that persists across every conversation.
Everything your agent needs to think
Not just storage. A cognitive layer that makes memories useful.
Semantic Search
Query by meaning, not keywords. Embeddings-powered retrieval that understands what your agent actually needs.
27 MCP Tools
observe(), query(), validate(), evolve(), wander(), believe(), and more. A full cognitive toolkit exposed via Model Context Protocol.
Session Continuity
Automatic context bridging across conversations. Your agent picks up exactly where it left off.
FSRS Scheduling
Spaced repetition for memory salience. Important memories surface first, stale ones decay gracefully.
Multi-Provider
Firestore or SQLite storage. Ollama, Vertex AI, or OpenAI embeddings. Swap providers without rewriting.
Type-Safe SDK
Full TypeScript. Every tool typed. Every response predictable. Build with confidence, not guesswork.
How it fits together
cortex-engine sits between your agent and its memory, handling storage, embeddings, and tool routing transparently.
Your Agent (Claude, GPT, Gemini, etc.)
|
v
+---------------------------+
| cortex-engine SDK |
| |
| observe() - query() |
| validate() - evolve() |
| wander() - believe() |
+--------+--------+--------+
| |
+----v--+ +---v-----------+
|Storage| |Embedding Engine|
| | | |
| SQLite | Ollama |
| Firestore| Vertex AI |
| | OpenAI |
+----+--+ +---+------------+
| |
v v
+---------------------------+
| MCP Server |
| 27 tools exposed via |
| Model Context Protocol |
+---------------------------+Get started in 30 seconds
One command. Full cognitive layer. No configuration required.