MCP Memento Memory Server

Get comprehensive onboarding protocol for Memento including tool usage guidance, retrieval flow optimization, and best practices. MEMENTO ONBOARDING PROTOCOL: 1. INITIALIZATION: Run memento_onboarding() at session start 2. RETRIEVAL FLOW: - Fact Check: Use search_mementos(tags=[...]) for simple identity/known facts - Complex Tasks: Use recall_mementos(query="...") for dev/architecture context - Fallback: If search fails, fallback to recall 3. AUTOMATIC STORAGE: Store via store_memento on git commits, bug fixes, version releases 4. ON-DEMAND TRIGGERS: Store instantly when user says "memento...", "remember...", etc. 5. MEMORY SCHEMA: Required tags (project, tech, category). Importance: 0.8+ (critical), 0.5 (standard) OPTIMIZED RETRIEVAL (Avoid 6+ tool calls): - Target: 1-3 tool calls for simple info - Maximum: 5 tool calls for complex tasks - Follow decision tree: Known tags → search_mementos, Conceptual → recall_mementos CRITICAL DISTINCTION: Memento vs Session memory - Memento: Long-term, cross-session, global scope - Session Memory: Temporary, project-specific, session-only USE memento_onboarding(topic="...") for specific guidance: - "protocol": Full onboarding protocol - "retrieval_flow": Optimized retrieval guide - "distinction": Memento vs Session memory - "examples": Practical examples - "best_practices": Usage guidelines

Primary tool for finding mementos using natural language queries. Optimized for fuzzy matching - handles plurals, tenses, and case variations automatically. BEST FOR: - Conceptual queries ("how does X work") - General exploration ("what do we know about authentication") - Fuzzy/approximate matching USE FOR: Long-term knowledge that survives across sessions. DO NOT USE FOR: Temporary session context or project-specific state. LESS EFFECTIVE FOR: - Acronyms (DCAD, JWT, API) - use search_mementos with tags instead - Proper nouns (company names, services) - Exact technical terms EXAMPLES: - recall_mementos(query="timeout fix") - find timeout-related solutions - recall_mementos(query="how does auth work") - conceptual query - recall_mementos(project_path="/app") - memories from specific project FALLBACK: If recall returns no relevant results, try search_mementos with tags filter.

Store a new memento with context and metadata. Required: type, title, content. Optional: id, tags, importance (0-1), context. USE FOR: Long-term knowledge that should survive across ALL sessions. DO NOT USE FOR: Temporary session state or project-specific context. LIMITS: - title: max 500 characters - content: max 50KB (50,000 characters) - tags: max 50 tags, 100 chars each - id: if provided, must be unique string identifier TAGGING BEST PRACTICE: - Always include acronyms AS TAGS (e.g., tags=["jwt", "auth"]) - Fuzzy search struggles with acronyms in content - Tags provide exact match fallback for reliable retrieval Types: solution, problem, error, fix, task, code_pattern, technology, command, file_context, workflow, project, general, conversation Note: `decision` is not a standalone type — use type="general" with tags=["decision", "architecture"]. Note: `pattern` is not a standalone type — use type="code_pattern". EXAMPLES: - store_memento(type="solution", title="Fixed Redis timeout", content="Increased timeout to 30s...", tags=["redis"], importance=0.8) - store_memento(type="error", title="OAuth2 auth failure", content="Error details...", tags=["auth", "oauth2"], id="custom-error-123") Returns memory_id. Use create_memento_relationship to link related memories.

Retrieve a specific memento by ID. Use when you have a memory_id from search results or store_memento. Set include_relationships=true (default) to see connected memories. EXAMPLE: get_memento(memory_id="abc-123")

Update an existing memento