memory
Memory system with three MCP tools: mcp__plugin_kg_kodegen__memory_list_libraries (discover namespaces), mcp__plugin_kg_kodegen__memory_memorize (store with embeddings), mcp__plugin_kg_kodegen__memory_recall (semantic search). Use for storing/retrieving knowledge by meaning. WHEN: User says "remember this", "recall", "what did I save", "my notes", "find my knowledge about". WHEN NOT: File operations (use fs_*), exact keyword search (use fs_search).
When & Why to Use This Skill
This Claude skill provides a sophisticated memory system powered by MCP tools, enabling semantic storage and retrieval of information. By utilizing vector embeddings, it allows users to save notes, project details, and snippets into isolated namespaces and recall them through natural language queries, effectively solving the challenge of long-term context retention and knowledge organization.
Use Cases
- Project Documentation: Store and retrieve complex architectural decisions, API specifications, and project-specific logic to maintain consistency throughout the development lifecycle.
- Personal Knowledge Base: Create a searchable digital brain for saving research findings, meeting summaries, and personal notes that can be accessed via meaning-based search.
- Code Snippet Management: Organize and find reusable code patterns and logic across various programming languages by describing the desired functionality instead of searching for exact syntax.
- Contextual Persistence: Bridge the gap between different sessions by memorizing user preferences, historical context, and specific instructions to provide more personalized and informed assistance.
| name | memory |
|---|---|
| description | > |
| Memory system with three MCP tools | mcp__plugin_kg_kodegen__memory_list_libraries (discover namespaces), mcp__plugin_kg_kodegen__memory_memorize (store with embeddings), mcp__plugin_kg_kodegen__memory_recall (semantic search). Use for storing/retrieving knowledge by meaning. |
| WHEN | User says "remember this", "recall", "what did I save", "my notes", "find my knowledge about". |
| WHEN NOT | File operations (use fs_*), exact keyword search (use fs_search). |
Memory System
Three MCP Tools
1. mcp__plugin_kg_kodegen__memory_list_libraries
Purpose: List all memory library names (namespaces)
Parameters: None - use {}
Returns: Array of library names
2. mcp__plugin_kg_kodegen__memory_memorize
Purpose: Store content with automatic embeddings
Parameters:
library(string, required) - Namespacecontent(string, required) - What to store
3. mcp__plugin_kg_kodegen__memory_recall
Purpose: Semantic search by meaning (not keywords)
Parameters:
library(string, required) - Which namespace to searchcontext(string, required) - Natural language querylimit(number, optional, default: 10) - Max results
When to Use Each
| User Says | Tool | Why |
|---|---|---|
| "remember this", "save this" | mcp__plugin_kg_kodegen__memory_memorize | Store new knowledge |
| "what did I save about X" | mcp__plugin_kg_kodegen__memory_recall | Find by semantic meaning |
| "what libraries exist" | mcp__plugin_kg_kodegen__memory_list_libraries | Discover namespaces |
Key Concepts
Semantic Search: Finds by meaning, not exact words. "authentication flow" matches "login process", "OAuth", "user sign-in" because semantically related.
Libraries as Namespaces: Each library is isolated. Use patterns like:
project-{name}for project knowledgesnippets-{lang}for code snippetsnotes-{context}for contextual notes
Content Best Practices:
- Include context, not just raw data
- One concept per memory
- Self-contained (understandable alone)
- Natural language with searchable terms
Common Workflows
Store:
{"library": "project-notes", "content": "Authentication uses OAuth2 with Google. Tokens in HTTP-only cookies, 24h timeout."}
Discover then Search:
// 1. List libraries
{}
// 2. Search specific library
{"library": "project-notes", "context": "authentication decisions", "limit": 5}
Cross-library Search: Use mcp__plugin_kg_kodegen__memory_list_libraries, then mcp__plugin_kg_kodegen__memory_recall from each relevant library.
Query Tips
✅ DO: "async HTTP requests with retry and timeout"
❌ DON'T: "http" or "retry"
Use natural language, describe what you're looking for. More context = better results.
Remember
- Libraries created on first use (no pre-creation needed)
- Memories are additive (storing doesn't replace)
- Embeddings are automatic
- Results ranked by semantic similarity