brainy/docs/conversation/MCP_INTEGRATION.md

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# MCP Integration - Claude Code Setup
**One command. Infinite memory.** This guide shows you how to give Claude Code infinite context and conversation history using Brainy's Model Control Protocol (MCP) integration.
## Quick Setup
### One-Time Configuration
```bash
# Install Brainy globally (if not already installed)
npm install -g @soulcraft/brainy
# Set up MCP server for Claude Code
brainy conversation setup
```
**That's it!** Claude Code now has infinite memory.
### What This Does
The setup command:
1. Creates `~/.brainy-memory/` directory
2. Initializes Brainy database with filesystem storage
3. Creates MCP server script
4. Registers server with Claude Code
5. Ready to use - no configuration needed
## How It Works
### Automatic Integration
Once set up, Claude Code **automatically**:
**On Every Message:**
- Saves your message with semantic embeddings
- Saves Claude's response with metadata
- Links code artifacts to conversations
- Tracks problem-solving phase and confidence
- Indexes everything for instant retrieval
**On Conversation Start:**
- Retrieves relevant past context
- Finds similar previous conversations
- Loads linked code artifacts
- Presents context to Claude seamlessly
**Result:** Claude never loses context or momentum, even across completely separate conversations.
### User Experience
**Before:**
```
You: "How do I implement JWT auth?"
Claude: [Implements authentication]
[Days later, new conversation]
You: "Can you fix the JWT token validation?"
Claude: "I don't have context about your JWT implementation..."
```
**After:**
```
You: "How do I implement JWT auth?"
Claude: [Implements authentication, saves to Brainy]
[Days later, new conversation]
You: "Can you fix the JWT token validation?"
Claude: "I found 3 related past conversations about JWT...
Here's the implementation from /auth/middleware.ts..."
[Full context automatically retrieved]
```
## MCP Tools
The MCP server exposes 6 conversation tools that Claude Code uses automatically:
### 1. conversation_save_message
Saves a message to conversation history.
**Used by:** Claude Code automatically after each message
**Parameters:**
- `content`: Message text
- `role`: 'user' | 'assistant' | 'system' | 'tool'
- `conversationId`: Conversation identifier
- `phase`: Problem-solving phase
- `confidence`: Confidence score
- `artifacts`: Array of artifact IDs
- `toolsUsed`: Tools used in this message
### 2. conversation_get_context
Retrieves relevant past context.
**Used by:** Claude Code at conversation start or when context is needed
**Parameters:**
- `query`: What to retrieve context for
- `limit`: Max messages (default: 10)
- `maxTokens`: Token budget (default: 50000)
- `relevanceThreshold`: Min similarity (default: 0.7)
- `includeArtifacts`: Include code/files
- `includeSimilarConversations`: Include similar past conversations
**Returns:**
- Ranked messages with relevance scores
- Linked artifacts
- Similar past conversations
- Metadata (query time, tokens, etc.)
### 3. conversation_search
Searches all conversations semantically.
**Used by:** When Claude needs to find specific past information
**Parameters:**
- `query`: Search query
- `role`: Filter by role
- `conversationId`: Filter by conversation
- `timeRange`: Time range filter
### 4. conversation_get_thread
Gets complete conversation thread.
**Used by:** When Claude needs full conversation history
**Parameters:**
- `conversationId`: Conversation ID
- `includeArtifacts`: Include linked artifacts
### 5. conversation_save_artifact
Saves code/file artifacts.
**Used by:** When Claude creates files
**Parameters:**
- `path`: File path
- `content`: File content
- `conversationId`: Conversation ID
- `messageId`: Message that created it
- `type`: 'code' | 'config' | 'data' | 'document'
- `language`: Programming language
### 6. conversation_find_similar
Finds similar past conversations.
**Used by:** For discovering related work
**Parameters:**
- `conversationId`: Conversation to find similar to
- `limit`: Max results
- `threshold`: Similarity threshold
## MCP Server Architecture
### Server Location
```
~/.brainy-memory/
├── mcp-server.js # MCP server script
└── data/ # Brainy database
├── nouns/ # Messages
├── verbs/ # Relationships
└── index/ # Search indexes
```
### Server Script
The generated server script (`~/.brainy-memory/mcp-server.js`):
```javascript
import { Brainy } from '@soulcraft/brainy'
import { BrainyMCPService } from '@soulcraft/brainy'
import { MCPConversationToolset } from '@soulcraft/brainy'
// Initialize Brainy
const brain = new Brainy({
storage: {
type: 'filesystem',
path: '~/.brainy-memory/data'
},
silent: true
})
await brain.init()
// Create MCP service
const mcpService = new BrainyMCPService(brain)
const conversationTools = new MCPConversationToolset(brain)
// Handle MCP requests via stdio
process.stdin.on('data', async (data) => {
const request = JSON.parse(data.toString())
let response
if (request.toolName?.startsWith('conversation_')) {
response = await conversationTools.handleRequest(request)
} else {
response = await mcpService.handleRequest(request)
}
process.stdout.write(JSON.stringify(response) + '\\n')
})
```
### Claude Code Configuration
Located at `~/.config/claude-code/mcp-servers.json`:
```json
{
"brainy-memory": {
"command": "node",
"args": ["~/.brainy-memory/mcp-server.js"],
"env": {
"NODE_ENV": "production"
}
}
}
```
## Advanced Configuration
### Custom Storage Location
Edit `~/.brainy-memory/mcp-server.js`:
```javascript
const brain = new Brainy({
storage: {
type: 'filesystem',
path: '/path/to/custom/location'
}
})
```
### Cloud Storage (Multi-Device Sync)
Use S3-compatible storage for sync across machines:
```javascript
const brain = new Brainy({
storage: {
type: 's3',
bucket: 'my-brainy-memory',
region: 'us-east-1'
}
})
```
**Requirements:** Set AWS credentials in environment:
```bash
export AWS_ACCESS_KEY_ID=xxx
export AWS_SECRET_ACCESS_KEY=yyy
```
### Memory Storage (Testing)
For testing or temporary use:
```javascript
const brain = new Brainy({
storage: { type: 'memory' }
})
```
**Note:** Memory storage is lost on server restart.
### Context Retrieval Options
Customize context retrieval behavior:
```javascript
const context = await conversationManager.getRelevantContext(query, {
limit: 15, // More messages
maxTokens: 80000, // Larger context window
relevanceThreshold: 0.6, // Lower threshold = more results
weights: {
semantic: 0.7, // Adjust relevance weights
temporal: 0.6,
graph: 0.4
}
})
```
## Troubleshooting
### Server Not Starting
**Check logs:**
```bash
# Server writes to stderr
tail -f ~/.brainy-memory/server.log
```
**Common issues:**
1. **Node version**: Requires Node.js 22 LTS
2. **Permissions**: Ensure ~/.brainy-memory is writable
3. **Port conflicts**: MCP uses stdio, no ports needed
### Claude Code Not Using Memory
**Verify setup:**
```bash
# Check MCP server is registered
cat ~/.config/claude-code/mcp-servers.json
# Test server manually
echo '{"type":"system_info","infoType":"version","requestId":"test","version":"1.0.0"}' | node ~/.brainy-memory/mcp-server.js
```
**Expected output:**
```json
{"success":true,"requestId":"test","version":"1.0.0","data":{"version":"1.0.0"}}
```
### Memory Not Persisting
**Check storage:**
```bash
# Verify data directory exists
ls -la ~/.brainy-memory/data/
# Check database files
du -sh ~/.brainy-memory/data/
```
**If empty:** Server may be using memory storage. Check `mcp-server.js` configuration.
### Performance Issues
**Optimize database:**
```bash
# Rebuild indexes
brainy conversation stats # This triggers index optimization
```
**Check size:**
```bash
# Show storage usage
du -sh ~/.brainy-memory/
```
**If too large:** Consider cloud storage or compaction strategies.
## CLI Commands
Manage conversations via CLI:
### View Statistics
```bash
brainy conversation stats
```
Output:
```
📊 Conversation Statistics
Overall:
Conversations: 42
Messages: 1,337
Total Tokens: 567,890
Avg Messages/Conversation: 31.8
Avg Tokens/Message: 425.1
By Role:
user: 650
assistant: 687
By Phase:
implementation: 423
planning: 201
testing: 98
```
### Search Messages
```bash
brainy conversation search -q "authentication" -l 10
```
### Get Context
```bash
brainy conversation context -q "JWT token validation" -l 15
```
### View Thread
```bash
brainy conversation thread -c conv_abc123
```
### Export Conversation
```bash
brainy conversation export -c conv_abc123 -o backup.json
```
### Import Conversation
```bash
brainy conversation import -o backup.json
```
## Security & Privacy
### Local-First by Default
- All data stored locally in `~/.brainy-memory/`
- No external services or APIs
- Complete privacy and control
### Data Encryption
For sensitive conversations, use encrypted filesystem:
```bash
# Create encrypted volume
hdiutil create -size 1g -encryption AES-256 -volname BrainyMemory ~/brainy-secure.dmg
# Mount and use
hdiutil attach ~/brainy-secure.dmg
brainy conversation setup --path /Volumes/BrainyMemory
```
### Access Control
MCP server runs with your user permissions. No additional authentication needed for local use.
## Next Steps
- [API Reference](./API_REFERENCE.md) - Complete API documentation
- [Examples](./EXAMPLES.md) - Usage examples and patterns
- [Advanced Features](./ADVANCED.md) - Advanced configuration and optimization
## Support
Issues or questions:
- GitHub: [soulcraftlabs/brainy/issues](https://github.com/soulcraftlabs/brainy/issues)
- Documentation: [docs.brainy.ai](https://docs.brainy.ai)