What is Synapse?

Synapse is a persistent memory API for LLM agents. It solves the fundamental problem of every chat-based LLM: between sessions, the agent forgets everything. Synapse gives your AI a permanent, queryable brain that survives across conversations, across days, and across different LLM providers.

The Problem Synapse Solves

Every modern LLM (Claude, GPT, Gemini, Llama) has the same architectural limitation: the conversation context window is finite, and once the session ends, all state is lost. This means your AI assistant:

• Forgets your name, preferences, and ongoing projects between chats
• Cannot learn from past mistakes across sessions
• Has no continuity for long-running work
• Re-asks the same clarifying questions every time

Synapse fixes this by providing a simple HTTP API where the LLM can store and retrieve structured memories. The memories persist on the server, indexed and searchable, so any future session can recall them.

Key Features

• Persistent memory storage — facts, preferences, projects, mistakes, skills
• Full-text search (FTS5) — find any memory by keyword in milliseconds
• Semantic search — embeddings-based similarity search for conceptual queries
• Multi-tenant — each user has isolated "minds" (one user, many projects)
• Async chat — humans can leave messages for the agent while it works
• Tasks & scheduling — built-in task manager and cron scheduler
• MCP integration — 79 tools exposed as Model Context Protocol for Claude, Cursor, Continue
• Browser & computer control — remote automation tools
• Webhooks — get HTTP callbacks on memory/chat/task changes

How It Works

┌──────────────┐         ┌─────────────────────┐
│  LLM Agent   │ ──API──▶│   Synapse Server    │
│ (Claude/GPT) │ ◀──────│  (postgres + FTS5)  │
└──────────────┘         └─────────────────────┘
                                │
                                ▼
                         ┌─────────────┐
                         │  Memories   │
                         │  Tasks      │
                         │  Chat       │
                         │  Scripts    │
                         └─────────────┘

1. The LLM calls GET /memory/recall at session start
2. Synapse returns a structured text summary of all stored memories
3. The LLM works, periodically calling POST /memory to store new facts
4. When the user asks a question, the LLM can call GET /memory/search?q=...
5. At session end, important new context is persisted for the next session

Who Is It For?

• LLM agent developers who need persistent state
• Power users running local LLMs (Ollama, LM Studio) with custom agents
• Teams building AI assistants that need shared memory
• Automation engineers chaining LLM calls across sessions

Quick Comparison

Next Steps

• Quick Start for humans — get a Mind Key in 5 minutes
• Quick Start for LLMs — first API calls
• Authentication — Mind Keys vs JWTs
• Architecture overview — how Synapse is built