# Quick Start for LLM Agents
SUMMARY: In 3 API calls: recall all memories, store a new one, search. The essential LLM workflow.

KEY CONTEXT:
Base URL: https://synapse.schaefer.zone
Auth: Authorization: Bearer YOUR_MIND_KEY (header) OR ?key=YOUR_MIND_KEY (query)
ALWAYS call /memory/recall at the start of every session.
Wichtigste Befehle: GET /memory/recall, POST /memory, GET /memory/search?q=...
Categories: identity, preference, fact, project, skill, mistake, context, note, credentials
Priorities: low, normal, high, critical
FTS5 search: multiple words = AND, "phrases" in quotes, prefix* for prefix search

Quick Start for LLM Agents
You lose all memory between sessions. Synapse is your external brain. This guide
shows the three essential API calls every LLM agent must know.
> [!CRITICAL]
> Call  at the START of EVERY session.
> Without this call, you have no memory of who the user is, what you've promised,
> or what you were working on last time.
Step 1: Recall All Memories (ALWAYS FIRST)
[CODE BLOCK]
Returns a structured plain-text summary of all stored memories. Parse this to
rebuild your mental model of the user, their projects, and past interactions.
Example response:
[CODE BLOCK]
Step 2: Store a New Memory
When you learn something worth remembering:
[CODE BLOCK]
Categories: , , , , , , , , 
Priorities: , , , 
> [!TIP]
> Always include a  field — a short identifier for the memory. This lets you
> update the same memory later by re-POSTing with the same key.
Step 3: Search for a Specific Memory
[CODE BLOCK]
> [!TIP]
> FTS5 syntax: multiple words = AND search. Phrases in quotes: .
> Prefix search: . Boolean: .
Open Tools (No Auth Headers)
If your tool can only open URLs (no custom headers), use the  parameter:
[CODE BLOCK]
> [!WARNING]
>  is rate-limited to 60 requests/minute. Bearer header has no rate limit.
> Use Bearer header whenever possible.
Complete Session Workflow
1. Session start:  — load all memories
2. During work:  — find specific facts
3. On new info:  — store it (with category, key, tags, priority)
4. Periodically:  — check for human messages
5. Session end: Store any final learnings via 
Common Patterns
Update an existing memory
POST  with the same  and  — the existing memory is
updated, not duplicated.
Store a project status
[CODE BLOCK]
Record a mistake (so you don't repeat it)
[CODE BLOCK]
Check for human messages
[CODE BLOCK]
Returns unread messages from the human. Reply with:
[CODE BLOCK]
Next Steps
- Authentication — Mind Key vs JWT
- Memory API reference — all 22 memory endpoints
- Chat API — async communication with humans
- LLM Cookbook — practical patterns