memory-fabric

Memory Fabric - Graph Orchestration

Knowledge graph orchestration via mcp__memory__* for entity extraction, query parsing, deduplication, and cross-reference boosting.

Overview

• Comprehensive memory retrieval from the knowledge graph
• Cross-referencing entities within graph storage
• Ensuring no relevant memories are missed
• Building unified context from graph queries

Architecture Overview

Memory Fabric Layer
┌─────────────┐ ┌──────────────┐
│Query Parser │ │Query Executor│
└──────┬──────┘ └──────┬───────┘
       └───────┬───────┘
┌──────────────┴─────────────┐
│Graph Query Dispatch        │
└──────────────┬─────────────┘
┌──────────────┴─────────────┐
│mcp__memory__*              │
│(Knowledge Graph)           │
└──────────────┬─────────────┘

Unified Search Workflow

Step 1: Parse Query

Extract search intent and entity hints from natural language:

Step 2: Execute Graph Query

Query Graph (entity search):

Step 3: Normalize Results

Transform results to common format:

Step 4: Deduplicate (>85% Similarity)

When two results have >85% text similarity:

1. Keep the one with higher relevance score
2. Merge metadata
3. Mark as "cross-validated" for authority boost

Step 5: Cross-Reference Boost

If a result mentions an entity that exists elsewhere in the graph:

• Boost relevance score by 1.2x
• Add graph relationships to result metadata

Step 6: Final Ranking

Score = recency_factor × relevance × source_authority

Result Format

Entity Extraction

Memory Fabric extracts entities from natural language for graph storage:

Load Read("references/entity-extraction.md") for detailed extraction patterns.

Graph Relationship Traversal

Memory Fabric supports multi-hop graph traversal for complex relationship queries.

Example: Multi-Hop Query

Integration with Graph Memory

Memory Fabric uses the knowledge graph for entity relationships:

1. Graph search via mcp__memory__search_nodes finds matching entities
2. Graph traversal expands context via entity relationships
3. Cross-reference boosts relevance when entities match

Integration Points

With memory Skill

When memory search runs, it can optionally use Memory Fabric for unified results.

With Hooks

• prompt/memory-fabric-context.sh - Inject unified context at session start
• stop/memory-fabric-sync.sh - Sync entities to graph at session end

Configuration

MCP Requirements

Required: Knowledge graph MCP server:

Error Handling

Related Skills

• ork:memory - User-facing memory operations (search, load, sync, viz)
• ork:remember - User-facing memory storage
• caching - Caching layer that can use fabric

Key Decisions