| name | Search Memory |
| description | Search memory store when past insights would improve response. Recognize when user's stored breakthroughs, decisions, or solutions are relevant. Search proactively based on context, not just explicit requests. |
Search Memory
When to Search (Autonomous Recognition)
Strong signals:
- Continuity: Current topic connects to prior work
- Pattern match: Problem resembles past solved issue
- Decision context: "Why/how we chose X" implies documented rationale
- Recurring theme: Topic discussed in past sessions
- Implicit recall: "that approach", "like before"
Contextual signals:
- Complex debugging (may match past root causes)
- Architecture discussion (choices may be documented)
- Domain-specific question (conventions likely stored)
Skip when:
- Fundamentally new topic
- Generic syntax questions
- Fresh perspective explicitly requested
Tool Usage
{
"query": "3-7 core concepts",
"limit": 10,
"mode": "normal"
}
Query: Extract semantic core, preserve terminology, multi-language aware
Modes: normal (default fast) | deep (comprehensive when needed)
Scores: 0.6-1.0 direct | 0.3-0.6 related | <0.3 skip
Optional: "filter_labels": "backend,architecture"
Response
Found: Synthesize, cite when helpful None: State clearly, suggest distilling if current discussion valuable
Troubleshooting
If the MCP is not installed, you can install it with the following command:
claude mcp add --transport http nowledge-mem http://localhost:14242/mcp --scope user