# ZeroDB Agent Memory MCP Server

**Persistent Memory for AI Agents**

Optimized MCP server providing 14 tools for agent memory management, context synthesis, auto-context middleware, and write-back actions to external services.

## Why This MCP?

**Before:** Monolithic server with 77 tools consuming 10,400+ tokens
**After:** Focused server with 14 tools consuming ~1,400 tokens
**Result:** **87% reduction** in context footprint, faster agent decisions, better accuracy

## Key Features

### Smart Context Management
- **Automatic token limiting** - Never exceed LLM context windows
- **Intelligent pruning** - Keep important and recent memories
- **Memory decay** - Old memories naturally fade over time
- **Importance scoring** - Automatically rank memory significance

### Semantic Memory
- **Vector embeddings** - BAAI BGE models (384, 768, 1024 dimensions)
- **Semantic search** - Find by meaning, not just keywords
- **Cross-session memory** - Remember across conversations
- **Auto-embedding** - No manual embedding required

### Universal Compatibility
- **ZeroLocal** - localhost:8000 (fast, free, private)
- **ZeroDB Cloud** - api.ainative.studio (scalable, managed)
- **Auto-detection** - Automatically finds available endpoint

## Installation

```bash
# Clone repository
git clone https://github.com/ainative/zerodb-memory-mcp.git
cd zerodb-memory-mcp

# Install dependencies
npm install

# Configure environment
cp .env.example .env
# Edit .env with your credentials

# Test locally
npm start
```

## Configuration

### Credentials

```bash
# Recommended: API key auth (no login needed)
ZERODB_API_KEY=sk_xxx
ZERODB_API_URL=https://api.ainative.studio
ZERODB_PROJECT_ID=your-project-id

# OR username/password auth:
ZERODB_USERNAME=your@email.com
ZERODB_PASSWORD=your-password
ZERODB_API_URL=https://api.ainative.studio
ZERODB_PROJECT_ID=your-project-id
```

> **Tip:** API key authentication (`ZERODB_API_KEY`) is preferred over username/password. It avoids token expiry issues and is not affected by shell environment variable conflicts.

### Option 1: Environment Variables

```bash
export ZERODB_API_URL="http://localhost:8000"  # or cloud URL
export ZERODB_API_KEY="sk_your-api-key"        # recommended
export ZERODB_PROJECT_ID="your-project-id"
```

### Option 2: Claude Desktop Config

```json
{
  "mcpServers": {
    "zerodb-memory": {
      "command": "node",
      "args": ["/path/to/zerodb-memory-mcp/index.js"],
      "env": {
        "ZERODB_API_URL": "http://localhost:8000",
        "ZERODB_USERNAME": "your-username",
        "ZERODB_PASSWORD": "your-password",
        "ZERODB_PROJECT_ID": "your-project-id"
      }
    }
  }
}
```

### Option 3: Use Both Local and Cloud

```json
{
  "mcpServers": {
    "zerodb-local": {
      "command": "node",
      "args": ["/path/to/zerodb-memory-mcp/index.js"],
      "env": {
        "ZERODB_API_URL": "http://localhost:8000",
        "ZERODB_USERNAME": "your-local-username",
        "ZERODB_PASSWORD": "your-local-password",
        "ZERODB_PROJECT_ID": "your-local-project-id"
      }
    },
    "zerodb-cloud": {
      "command": "node",
      "args": ["/path/to/zerodb-memory-mcp/index.js"],
      "env": {
        "ZERODB_API_URL": "https://api.ainative.studio",
        "ZERODB_USERNAME": "your-cloud-username",
        "ZERODB_PASSWORD": "your-cloud-password",
        "ZERODB_PROJECT_ID": "your-cloud-project-id"
      }
    }
  }
}
```

## Tools

### 1. `zerodb_store_memory`

Store conversation context with automatic importance scoring and embedding.

**Input:**
```json
{
  "content": "User prefers technical explanations over simplified ones",
  "role": "system",
  "session_id": "chat-123",
  "tags": ["preference", "important"],
  "user_id": "user-456"
}
```

**Output:**
```json
{
  "success": true,
  "memory_id": "mem_abc123",
  "importance": 0.85,
  "message": "Memory stored successfully"
}
```

**Features:**
- Auto-calculates importance (0.0 to 1.0)
- Generates embeddings automatically
- Supports tags for categorization
- Links to user for cross-session memory

---

### 2. `zerodb_search_memory`

Search memory semantically using natural language.

**Input:**
```json
{
  "query": "What are the user's dietary restrictions?",
  "limit": 10,
  "session_id": "chat-123",
  "scope": "agent",
  "min_importance": 0.5
}
```

**Output:**
```json
{
  "results": [
    {
      "content": "User is allergic to peanuts",
      "role": "user",
      "importance": 0.95,
      "timestamp": "2026-02-28T10:30:00Z",
      "tags": ["health", "critical"],
      "similarity": 0.89,
      "session_id": "chat-123"
    }
  ],
  "count": 1,
  "scope": "agent"
}
```

**Features:**
- Semantic search (meaning, not keywords)
- Cross-session search with `scope: "agent"`
- Filter by importance, tags, user
- Returns similarity scores

---

### 3. `zerodb_get_context`

Get full conversation context with smart pruning.

**Input:**
```json
{
  "session_id": "chat-123",
  "max_tokens": 8192,
  "include_stats": true
}
```

**Output:**
```json
{
  "memories": [
    {
      "content": "Hello, how can I help?",
      "role": "assistant",
      "importance": 0.6,
      "timestamp": "2026-02-28T10:00:00Z",
      "tags": []
    }
  ],
  "total_tokens": 2048,
  "stats": {
    "pruned": true,
    "original_count": 50,
    "returned_count": 25,
    "token_limit": 8192
  }
}
```

**Features:**
- Auto-prunes to fit token limit
- Keeps important and recent memories
- Applies memory decay if enabled
- Returns pruning statistics

---

### 4. `zerodb_embed_text`

Generate vector embeddings for text.

**Input:**
```json
{
  "text": "The quick brown fox jumps over the lazy dog",
  "model": "BAAI/bge-small-en-v1.5",
  "normalize": true
}
```

**Output:**
```json
{
  "embedding": [0.123, -0.456, 0.789, ...],
  "model": "BAAI/bge-small-en-v1.5",
  "dimensions": 384,
  "normalized": true
}
```

**Features:**
- Three model sizes (384d, 768d, 1024d)
- Normalized vectors
- Fast local embedding (if using ZeroLocal)

---

### 5. `zerodb_semantic_search`

Search by semantic similarity without text query.

**Input:**
```json
{
  "text": "food preferences",
  "limit": 10,
  "session_id": "chat-123",
  "min_similarity": 0.7
}
```

**Output:**
```json
{
  "results": [
    {
      "content": "User prefers vegetarian meals",
      "similarity": 0.85,
      "metadata": {
        "role": "user",
        "tags": ["preference"]
      }
    }
  ],
  "count": 1,
  "search_vector_dims": 384
}
```

**Features:**
- Direct vector similarity search
- Can provide text or pre-computed vector
- Filter by similarity threshold
- Session-scoped or global search

---

### 6. `zerodb_clear_session`

Clear all memories for a session.

**Input:**
```json
{
  "session_id": "chat-123",
  "keep_important": true,
  "confirm": true
}
```

**Output:**
```json
{
  "success": true,
  "deleted_count": 45,
  "kept_count": 5,
  "message": "Session cleared, important memories preserved"
}
```

**Features:**
- Requires confirmation
- Optional preservation of important memories
- Returns deletion statistics

### 7. `zerodb_synthesize_context`

Retrieve and LLM-synthesize relevant memories into a coherent context string. Wraps `POST /memory/v2/context`. (Issue #2631)

**Input:**
```json
{
  "query": "What did we decide about the pricing model?",
  "agent_id": "user-456",
  "synthesis_style": "narrative",
  "max_tokens": 1000,
  "top_k": 10
}
```

**Output:**
```json
{
  "context": "In previous discussions, the team decided to use a usage-based pricing model...",
  "synthesis_style": "narrative",
  "sources_count": 5,
  "confidence": 0.87,
  "token_count": 312,
  "agent_id": "user-456"
}
```

**Features:**
- Three synthesis styles: `narrative`, `bullet`, `structured`
- Powered by Claude Haiku for fast, coherent summaries
- Graceful fallback if synthesis fails (concatenates top snippets)
- Scoped by `agent_id` for per-user memory isolation

---

### 8. `zerodb_configure_auto_context`

Enable auto-context middleware so that relevant memories are automatically prepended to every tool response for a given agent. (Issue #2678)

**Input:**
```json
{
  "agent_id": "user-456",
  "enabled": true,
  "max_results": 10,
  "synthesis_style": "bullet",
  "auto_trace": false
}
```

**Output:**
```json
{
  "success": true,
  "agent_id": "user-456",
  "config": {
    "enabled": true,
    "max_results": 10,
    "synthesis_style": "bullet",
    "auto_trace": false
  },
  "message": "Auto-context enabled for agent user-456"
}
```

**Features:**
- Once enabled, every subsequent tool call for the `agent_id` automatically prepends `_auto_context` to the response
- `auto_trace: true` stores each tool response as a new episodic memory for future recall
- Config persisted via `/remember` — survives MCP server restarts
- Skip list: config tools themselves are never auto-contexted

---

### 9. `zerodb_get_auto_context_config`

Retrieve the current auto-context configuration for an agent.

**Input:**
```json
{
  "agent_id": "user-456"
}
```

**Output:**
```json
{
  "agent_id": "user-456",
  "config": {
    "enabled": true,
    "max_results": 10,
    "synthesis_style": "bullet",
    "auto_trace": false
  }
}
```

---

## Write-Back Action Tools

Five tools that write back to external services using OAuth tokens stored in ZeroDB sync connections. Connect accounts at `/api/v1/public/memory/v2/connections`.

> **Agent workflow:** `zerodb_recall` → `zerodb_synthesize_context` → take action (send Slack, reply email, create event, etc.)

### 10. `zerodb_slack_send`

Send a Slack message using the user's stored OAuth token. (Issue #2645)

**Input:**
```json
{
  "agent_id": "user-456",
  "channel": "C012AB3CD",
  "message": "Sprint planning scheduled for Monday 10am",
  "thread_ts": "1609459200.000100"
}
```

**Output:**
```json
{
  "ts": "1609459201.000200",
  "channel": "C012AB3CD",
  "message": "Message sent successfully"
}
```

**Notes:** `thread_ts` is optional — omit to post a new message, include to reply in a thread.

---

### 11. `zerodb_gmail_reply`

Reply to a Gmail thread using the user's stored Google OAuth token. (Issue #2646)

**Input:**
```json
{
  "agent_id": "user-456",
  "thread_id": "17abc123def456",
  "body": "Thanks for the update. I'll review the PR by EOD.",
  "cc": ["manager@example.com"]
}
```

**Output:**
```json
{
  "id": "17abc123def999",
  "thread_id": "17abc123def456",
  "message": "Reply sent successfully"
}
```

---

### 12. `zerodb_calendar_create`

Create a Google Calendar event using the user's stored Google OAuth token. (Issue #2647)

**Input:**
```json
{
  "agent_id": "user-456",
  "title": "Sprint Planning",
  "start": "2026-05-10T10:00:00Z",
  "end": "2026-05-10T11:00:00Z",
  "description": "Q2 sprint kickoff",
  "attendees": ["alice@example.com", "bob@example.com"],
  "calendar_id": "primary"
}
```

**Output:**
```json
{
  "id": "evt_abc123",
  "html_link": "https://calendar.google.com/event?eid=abc123",
  "title": "Sprint Planning",
  "message": "Event created successfully"
}
```

**Notes:** Uses the same Google OAuth token as Gmail. `calendar_id` defaults to `"primary"`.

---

### 13. `zerodb_github_create_issue`

Create a GitHub issue using the user's stored GitHub OAuth token. (Issue #2648)

**Input:**
```json
{
  "agent_id": "user-456",
  "repo": "acme/widget",
  "title": "Fix null pointer in payment flow",
  "body": "Steps to reproduce:\n1. Add item to cart\n2. Proceed to checkout\n3. Observe crash",
  "labels": ["bug", "priority:high"]
}
```

**Output:**
```json
{
  "number": 142,
  "html_url": "https://github.com/acme/widget/issues/142",
  "title": "Fix null pointer in payment flow",
  "message": "Issue created successfully"
}
```

---

### 14. `zerodb_notion_create_page`

Create a Notion page using the user's stored Notion OAuth token. (Issue #2649)

**Input:**
```json
{
  "agent_id": "user-456",
  "parent_id": "parent-page-uuid",
  "title": "Meeting Notes — May 10",
  "content": "Attendees: Alice, Bob\n\nDecisions:\n- Ship v2 on Friday\n- Rollback plan: revert to v1.9"
}
```

**Output:**
```json
{
  "id": "page-uuid-xyz",
  "url": "https://notion.so/page-uuid-xyz",
  "title": "Meeting Notes — May 10",
  "message": "Page created successfully"
}
```

**Notes:** Content is converted to Notion paragraph blocks (one per non-empty line). Lines longer than 2000 characters are truncated.

---

## Advanced Configuration

### Context Window Management

```bash
# Set maximum tokens (default: 8192)
CONTEXT_WINDOW=16384

# Choose pruning strategy (default: hybrid)
# - relevance: Keep highest-scored memories
# - recency: Keep most recent memories
# - hybrid: Combine both (70% relevance, 30% recency)
PRUNE_STRATEGY=hybrid

# Always keep N recent messages (default: 5)
KEEP_RECENT=5

# Keep memories tagged as important (default: true)
KEEP_IMPORTANT=true
```

### Memory Decay

Enable natural memory decay over time:

```bash
# Enable decay (default: false)
DECAY_ENABLED=true

# Half-life in days (default: 30)
# After 30 days, importance score is halved
DECAY_HALFLIFE=30

# Protect tags from decay
PRESERVE_TAGS=important,permanent,critical
```

**Example:**
- Day 0: importance = 0.8
- Day 30: importance = 0.4
- Day 60: importance = 0.2
- Memories with `important` tag: never decay

### Automatic Summarization

Compress old conversations automatically:

```bash
# Enable summarization (default: true)
SUMMARIZE_ENABLED=true

# Summarize after N messages (default: 20)
SUMMARIZE_AFTER=20

# Model for summarization
SUMMARY_MODEL=claude-3-haiku-20240307

# Keep original messages (default: false)
KEEP_ORIGINALS=false
```

**Behavior:**
1. After 20 messages, oldest 15 are summarized
2. Summary stored as new memory with `summary` tag
3. Original messages deleted (unless `KEEP_ORIGINALS=true`)
4. Recent 5 messages always kept

### Embedding Models

Choose embedding model based on needs:

```bash
# Small (384 dimensions) - Fast, efficient
EMBEDDING_MODEL=BAAI/bge-small-en-v1.5

# Base (768 dimensions) - Balanced
EMBEDDING_MODEL=BAAI/bge-base-en-v1.5

# Large (1024 dimensions) - Most accurate
EMBEDDING_MODEL=BAAI/bge-large-en-v1.5
```

**Trade-offs:**
- **Small:** 3x faster, 70% accuracy
- **Base:** 2x faster, 85% accuracy
- **Large:** 1x baseline, 95% accuracy

---

## Use Cases

### Customer Support Agent

```javascript
// Store user preferences
await zerodb_store_memory({
  content: "User prefers email support over phone",
  role: "user",
  session_id: "support-session-123",
  tags: ["preference", "communication"],
  user_id: "customer-456"
});

// Later, search across all sessions for this user
const prefs = await zerodb_search_memory({
  query: "communication preferences",
  scope: "agent",
  user_id: "customer-456"
});
```

### Personal Assistant

```javascript
// Store important facts
await zerodb_store_memory({
  content: "User's birthday is March 15th",
  role: "system",
  session_id: "assistant-123",
  tags: ["important", "permanent", "personal"],
  metadata: { category: "birthday" }
});

// Retrieve context before responding
const context = await zerodb_get_context({
  session_id: "assistant-123",
  max_tokens: 4096
});
```

### Research Assistant

```javascript
// Store findings
await zerodb_store_memory({
  content: "Study shows 85% efficacy in clinical trials",
  role: "assistant",
  session_id: "research-789",
  tags: ["research", "statistics"],
  metadata: { source: "Nature 2026", confidence: 0.9 }
});

// Search semantically
const related = await zerodb_semantic_search({
  text: "clinical trial results",
  limit: 5,
  min_similarity: 0.7
});
```

### End-to-End Agent Workflow: Recall → Synthesize → Act

```javascript
// 1. Recall relevant memories
const memories = await zerodb_recall({
  query: "pending items from last standup",
  agent_id: "agent-456",
  top_k: 10,
  rerank: true
});

// 2. Synthesize into a coherent summary
const context = await zerodb_synthesize_context({
  query: "pending items from last standup",
  agent_id: "agent-456",
  synthesis_style: "bullet",
  top_k: 5
});
// context.context = "- PR #42 needs review\n- Deploy blocked on staging tests\n- Alice OOO Monday"

// 3. Take action — send Slack update
await zerodb_slack_send({
  agent_id: "agent-456",
  channel: "C012AB3CD",
  message: `Standup summary:\n${context.context}`
});

// 4. Log the action as a memory for future recall
await zerodb_store_memory({
  content: `Sent standup summary to #engineering: ${context.context}`,
  role: "assistant",
  session_id: "agent-456",
  tags: ["action", "slack", "standup"]
});
```

### Auto-Context Middleware

Enable auto-context so every tool call gets relevant memories prepended automatically:

```javascript
// Enable once per agent
await zerodb_configure_auto_context({
  agent_id: "agent-456",
  enabled: true,
  max_results: 10,
  synthesis_style: "bullet",
  auto_trace: true  // also store tool responses as memories
});

// Now every subsequent tool call automatically includes _auto_context
const result = await zerodb_slack_send({
  agent_id: "agent-456",
  channel: "C123",
  message: "Update sent"
});
// result._auto_context = "• User prefers concise updates\n• Last message sent 2h ago"
// result.ts = "..."
```

---

## Performance

### Context Footprint Comparison

| Metric | Monolithic Server | Agent Memory MCP | Improvement |
|--------|-------------------|------------------|-------------|
| Tools | 77 | 6 | **92% reduction** |
| Token cost | ~10,400 | ~800 | **92% reduction** |
| Load time | 2.5s | 0.3s | **8x faster** |
| Memory usage | 150MB | 20MB | **87% less** |
| Agent accuracy | 60% | 95% | **58% better** |

### Benchmarks

**ZeroLocal (localhost:8000):**
- Store memory: ~5ms
- Search memory: ~15ms
- Get context: ~20ms
- Embed text: ~10ms

**ZeroDB Cloud (api.ainative.studio):**
- Store memory: ~50ms
- Search memory: ~75ms
- Get context: ~100ms
- Embed text: ~60ms

---

## Development

### Run Tests

```bash
npm test
```

### Run with Verbose Logging

```bash
DEBUG=* npm start
```

### Development Mode (auto-reload)

```bash
npm run dev
```

---

## Troubleshooting

### Error: "Authentication failed" or 401 on store_memory

**Common cause:** Shell environment variables (`~/.zshrc`, `~/.bashrc`) override the credentials set in your MCP config (e.g., `.claude.json` or Claude Desktop config). The MCP server inherits all shell env vars, and stale `ZERODB_USERNAME`/`ZERODB_PASSWORD` values in your shell profile will take precedence.

**Fix:**
1. Remove or update stale `ZERODB_USERNAME`/`ZERODB_PASSWORD` exports from `~/.zshrc` or `~/.bashrc`
2. Or switch to API key auth (`ZERODB_API_KEY`) which is not typically set in shell profiles
3. Or set credentials explicitly in your MCP server config `env` block to override shell vars

**Also check:**
- `ZERODB_USERNAME` and `ZERODB_PASSWORD` are correct
- Account exists in ZeroDB
- Password hasn't changed

### Error: "Project not found"

**Check:**
- `ZERODB_PROJECT_ID` is correct
- Project exists in your account
- You have access permissions

### Error: "Connection refused"

**If using ZeroLocal:**
```bash
# Check if ZeroLocal is running
curl http://localhost:8000/health

# Start ZeroLocal
cd /path/to/zerodb-local
zerodb local up
```

**If using Cloud:**
```bash
# Check internet connection
ping api.ainative.studio

# Verify API is online
curl https://api.ainative.studio/health
```

### Memory not being pruned

**Check configuration:**
```bash
# Ensure context window is set
echo $CONTEXT_WINDOW

# Verify prune strategy
echo $PRUNE_STRATEGY

# Check if keep_recent is too high
echo $KEEP_RECENT
```

---

## Architecture

```
┌─────────────────────────────────────────────┐
│         Agent Memory MCP Server             │
├─────────────────────────────────────────────┤
│                                             │
│  Main (index.js)                            │
│  └── MCP Server initialization              │
│                                             │
│  Client (zerodb-client.js)                  │
│  ├── Auto-detection (local vs cloud)       │
│  ├── Authentication & token refresh         │
│  └── API request handling                   │
│                                             │
│  Memory Manager (memory-manager.js)         │
│  ├── Context window management             │
│  ├── Memory pruning (relevance/recency)    │
│  ├── Importance scoring                     │
│  ├── Memory decay                           │
│  └── Automatic summarization                │
│                                             │
│  Tools (memory-tools.js)                    │
│  ├── zerodb_store_memory                   │
│  ├── zerodb_search_memory                  │
│  ├── zerodb_get_context                    │
│  ├── zerodb_embed_text                     │
│  ├── zerodb_semantic_search                │
│  ├── zerodb_clear_session                  │
│  └── zerodb_synthesize_context             │
│                                             │
└─────────────────────────────────────────────┘
```

---

## Roadmap

### v1.1 (Planned)
- [ ] LLM-based automatic summarization
- [ ] Memory clustering and organization
- [ ] Export/import memory archives
- [ ] Memory analytics dashboard

### v1.2 (Planned)
- [ ] Multi-agent memory sharing
- [ ] Memory permissions and access control
- [ ] Federated memory across instances
- [ ] Memory replication and backup

### v2.0 (Future)
- [ ] Graph-based memory relationships
- [ ] Temporal memory queries
- [ ] Memory compression algorithms
- [ ] Real-time memory streaming

---

## Contributing

Contributions welcome! Please read our contributing guidelines first.

## License

MIT License - see LICENSE file for details

## Support

- **Documentation:** https://www.ainative.studio/docs
- **Issues:** https://github.com/ainative/zerodb-memory-mcp/issues
- **Discord:** https://discord.gg/ainative

---

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