Documentation
Persistent AI memory, stored on your machine
Getting Started Connect Claude.ai Tools Reference (11 tools) Access Control Troubleshooting

Getting Started

1. Install MNESIQ

npm install -g mnesiq
mnesiq

This starts the MNESIQ server at http://localhost:4200. Open it in your browser. The setup wizard will detect your hardware and recommend a model, or you can add a cloud API key.

2. Connect to the Relay

The relay makes your MNESIQ reachable from the internet so Claude.ai and other cloud LLMs can connect.

  1. Open MNESIQ at localhost:4200
  2. Click Gateway in the top bar
  3. Go to the Relay tab
  4. Sign up with your email
  5. You'll get a public endpoint like yourname.mcp.amnesiaiq.ai

The relay is zero-knowledge. It routes encrypted WireGuard traffic without seeing, storing, or logging your memory data.

Connect Claude.ai

From the Connector Directory

  1. In Claude.ai, go to Settings → Connectors
  2. Find MNESIQ and click Add
  3. Authorize on the consent page with your relay account
  4. Done — Claude now has 11 memory tools

Custom Connector

  1. In Claude.ai, go to Settings → Connectors → Add Custom
  2. Enter URL: https://api.amnesiaiq.ai/mcp
  3. Leave Client ID and Secret blank (auto-registered via OAuth)
  4. Authorize with your relay account

What Claude Can Do

Once connected, Claude automatically:

Tools Reference

Read Tools

recall_context read
Search memories by natural language query. Returns the most relevant matches with confidence scores.
Parameters: query (required), domain, category, max_results
get_passport read
Generate a signed context bundle of your most relevant memories for system prompt injection.
Parameters: domain, max_tokens
get_full_context read
Passport + proactive items combined. The recommended session-start call.
Parameters: topic, domain
get_proactive_context read
High-priority context: active goals, risk rules, approaching deadlines.
Parameters: conversation_summary (required), domain
analyze_for_extraction read
Analyze conversation text for extractable facts before storing. Preview without committing.
Parameters: text (required)

Write Tools

remember_context write
Store a memory. Categories: fact, preference, goal, skill, behavior_pattern, relationship, opinion, list_item.
Parameters: content (required), category, domain, confidence, clearance
extract_from_conversation write
Batch-extract and store multiple memories from a conversation segment.
Parameters: memories (required, array), domain
set_intent write
Create a goal with lifecycle tracking: stated → active → fulfilled / deferred / abandoned.
Parameters: content (required), domain, target_date, fulfillment_criteria
update_intent_status write
Transition a goal through its lifecycle.
Parameters: intent_id (required), status (required), evidence
manage_list write
Add, complete, or dismiss items from named lists (todo, reading, watch, shopping, etc.).
Parameters: list_name (required), action (required), content, item_id
consolidate_context destructive
Compress old granular memories into higher-order insights. Source memories are archived.
Parameters: domain, category

Access Control

Clearance Levels

Each connected LLM is assigned a clearance level. Higher clearance sees everything below it.

Compartments

Compartments restrict topic access. A client assigned to "work" only sees memories from clients that share the "work" compartment. Use "all" for unrestricted access.

Memories inherit the clearance of the client that stored them. The LLM never knows its clearance level — all gating happens server-side. Configure access in the MNESIQ Gateway → Clients tab.

Troubleshooting

Claude says "Authorization failed"

Tools return errors

Memories not appearing

Relay won't connect

Slow first response

The first memory operation may take a few seconds while the embedding model loads. Subsequent operations are fast. With Ollama running locally, embeddings are nearly instant.