docs: add doobidoo/mcp-memory-service documentation (semantic memory)
- Add comprehensive section in ultimate-guide.md (L.6385-6523) - Document 3 backends: sqlite_vec, cloudflare, hybrid - List 12 MCP tools with descriptions - Add environment variables reference - Include multi-client sync patterns (same machine vs multi-device) - Add disclaimer: under testing, not yet validated in production - Update reference.yaml with 8 new entries - Add to cheatsheet.md and mcp.json template Complements Serena (key-value) with semantic search capabilities. Co-Authored-By: Claude <noreply@anthropic.com>
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Florian BRUNIAUX
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@ -33,6 +33,11 @@
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"command": "grepai",
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"args": ["mcp-serve"],
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"description": "Semantic code search and call graph analysis (requires Ollama)"
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},
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"doobidoo-memory": {
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"command": "memory",
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"args": ["server"],
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"description": "Semantic memory with cross-session search (complements Serena)"
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}
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}
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}
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@ -212,6 +212,7 @@ Model: Sonnet | Ctx: 89.5k | Cost: $2.11 | Ctx(u): 56.0%
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| **Sequential** | Structured reasoning |
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| **Playwright** | Browser automation |
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| **Postgres** | Database queries |
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| **doobidoo** | Semantic memory + multi-client + Knowledge Graph |
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**Serena memory**: `write_memory()` / `read_memory()` / `list_memories()`
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@ -6382,6 +6382,145 @@ mgrep "code that handles user authentication"
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- Visual validation
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- Browser debugging
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### doobidoo Memory Service (Semantic Memory)
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> **⚠️ Status: Under Testing** - This MCP server is being evaluated. The documentation below is based on the official repository but hasn't been fully validated in production workflows yet. Feedback welcome!
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**Purpose**: Persistent semantic memory with cross-session search and multi-client support.
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**Why doobidoo complements Serena**:
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- Serena: Key-value memory (`write_memory("key", "value")`) - requires knowing the key
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- doobidoo: Semantic search (`retrieve_memory("what did we decide about auth?")`) - finds by meaning
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| Feature | Serena | doobidoo |
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|---------|--------|----------|
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| Memory storage | Key-value | Semantic embeddings |
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| Search by meaning | No | Yes |
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| Multi-client | Claude only | 13+ apps |
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| Dashboard | No | Knowledge Graph |
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| Symbol indexation | Yes | No |
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**Storage Backends**:
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| Backend | Usage | Performance |
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|---------|-------|-------------|
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| `sqlite_vec` (default) | Local, lightweight | <10ms queries |
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| `cloudflare` | Cloud, multi-device sync | Edge performance |
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| `hybrid` | Local fast + cloud background sync | 5ms local |
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**Data Location**: `~/.mcp-memory-service/memories.db` (SQLite with vector embeddings)
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**MCP Tools Available** (12 unified tools):
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| Tool | Description |
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|------|-------------|
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| `store_memory` | Store with tags, type, metadata |
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| `retrieve_memory` | Semantic search (top-N by similarity) |
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| `search_by_tag` | Exact tag matching (OR/AND logic) |
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| `delete_memory` | Delete by content_hash |
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| `list_memories` | Paginated browsing with filters |
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| `check_database_health` | Stats, backend status, sync info |
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| `get_cache_stats` | Server performance metrics |
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| `memory_graph:connected` | Find connected memories |
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| `memory_graph:path` | Shortest path between memories |
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| `memory_graph:subgraph` | Subgraph around a memory |
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**Installation**:
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```bash
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# Quick install (local SQLite backend)
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pip install mcp-memory-service
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python -m mcp_memory_service.scripts.installation.install --quick
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# Team/Production install (more options)
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git clone https://github.com/doobidoo/mcp-memory-service.git
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cd mcp-memory-service
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python scripts/installation/install.py
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# → Choose: cloudflare or hybrid for multi-device sync
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```
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**Configuration** (add to MCP config):
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```json
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{
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"mcpServers": {
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"memory": {
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"command": "memory",
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"args": ["server"]
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}
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}
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}
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```
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**Configuration with environment variables** (for team/cloud sync):
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```json
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{
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"mcpServers": {
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"memory": {
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"command": "memory",
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"args": ["server"],
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"env": {
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"MCP_MEMORY_STORAGE_BACKEND": "hybrid",
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"MCP_HTTP_ENABLED": "true",
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"MCP_HTTP_PORT": "8000",
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"CLOUDFLARE_API_TOKEN": "your-token",
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"CLOUDFLARE_ACCOUNT_ID": "your-account-id"
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}
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}
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}
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}
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```
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**Key Environment Variables**:
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| Variable | Default | Description |
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|----------|---------|-------------|
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| `MCP_MEMORY_STORAGE_BACKEND` | `sqlite_vec` | Backend: sqlite_vec, cloudflare, hybrid |
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| `MCP_HTTP_ENABLED` | `true` | Enable dashboard server |
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| `MCP_HTTP_PORT` | `8000` | Dashboard port |
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| `MCP_OAUTH_ENABLED` | `false` | Enable OAuth for team auth |
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| `MCP_HYBRID_SYNC_INTERVAL` | `300` | Sync interval in seconds |
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**Usage**:
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```
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# Store a decision with tags
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store_memory("We decided to use FastAPI for the REST API", tags=["architecture", "api"])
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# Semantic search (finds by meaning, not exact match)
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retrieve_memory("what framework for API?")
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→ Returns: "We decided to use FastAPI..." with similarity score
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# Search by tag
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search_by_tag(["architecture"])
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# Check health
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check_database_health()
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```
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**Multi-Client Sync**:
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```
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# Same machine: all clients share ~/.mcp-memory-service/memories.db
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Claude Code ──┐
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Cursor ───────┼──► Same SQLite file
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VS Code ──────┘
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# Multi-device: use Cloudflare backend
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Device A ──┐
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Device B ──┼──► Cloudflare D1 + Vectorize
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Device C ──┘
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```
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**When to use which**:
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- **Serena**: Symbol navigation, code indexation, key-value memory with known keys
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- **doobidoo**: Cross-session decisions, "what did we decide about X?", multi-IDE sharing
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**Dashboard**: Access at http://localhost:8000 after starting the server.
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> **Source**: [doobidoo/mcp-memory-service GitHub](https://github.com/doobidoo/mcp-memory-service) (791 stars, v10.0.2)
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</details>
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## 8.3 Configuration
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@ -146,6 +146,7 @@ deep_dive:
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mcp_servers: 5984
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serena_indexation: 6078
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serena_mcp: 6037
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doobidoo_memory_mcp: 6385
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mcp_config: 6149
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mcp_security: 6517
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cicd: 6835
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@ -338,6 +339,13 @@ permissions:
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# ════════════════════════════════════════════════════════════════
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mcp:
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serena: "symbol search + session memory (write_memory/read_memory) + project indexation"
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doobidoo_memory: "semantic memory search + Knowledge Graph dashboard + 13+ clients (⚠️ under testing)"
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doobidoo_install: "pip install mcp-memory-service && python -m mcp_memory_service.scripts.installation.install --quick"
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doobidoo_dashboard: "http://localhost:8000"
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doobidoo_vs_serena: "Serena=key-value (requires known key), doobidoo=semantic search (finds by meaning)"
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doobidoo_backends: "sqlite_vec (local), cloudflare (multi-device), hybrid (local+cloud sync)"
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doobidoo_tools: "store_memory, retrieve_memory, search_by_tag, delete_memory, list_memories, check_database_health, memory_graph"
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doobidoo_data_location: "~/.mcp-memory-service/memories.db"
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serena_indexation: "uvx --from git+https://github.com/oraios/serena serena project index [--force-full|--incremental] [--parallel N]"
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serena_cache: ".serena/cache/typescript/ (add to .gitignore)"
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context7: "library docs lookup"
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