M.I.M.I.R - Multi-agent Intelligent Memory & Insight Repository

# Referenced Documentation Index This document catalogs all internal documentation files referenced during the competitive analysis for Mimir's memory bank capabilities. --- ## 1. AGENTS.md **File Path:** `AGENTS.md` **Description:** Primary documentation for AI agents working in the Mimir repository. Explains the Graph-RAG TODO tracking system, MCP tools, and multi-agent orchestration capabilities. **Relevance:** Core reference for understanding Mimir's unique features (TODO management, memory offloading, multi-agent workflows). **Key Sections:** - MCP Tools (13 total) - Memory Operations (node, edge, batch, lock, clear, get_task_context) - File Indexing System (index_folder, remove_folder, list_folders) - Vector Search (vector_search_nodes, get_embedding_stats) - TODO Management (todo, todo_list) - Usage Patterns (Single Agent vs. Multi-Agent) **Summary:** Essential for positioning Mimir against pure vector databases. Highlights capabilities not found in competitors (integrated TODO tracking, multi-agent coordination, MCP integration). --- ## 2. MULTI_AGENT_GRAPH_RAG.md **File Path:** `docs/architecture/MULTI_AGENT_GRAPH_RAG.md` **Description:** Complete architecture specification for Mimir's Graph-RAG system with multi-agent orchestration (v3.1). **Relevance:** Technical foundation for understanding Mimir's architecture compared to competitors. **Key Sections:** - Graph-RAG Architecture - PM → Worker → QC Agent Flow - Context Isolation Mechanisms - Optimistic Locking for Concurrent Agents - Neo4j Graph Schema **Summary:** Referenced for architectural comparisons in technical report. Explains how Mimir combines graph databases with vector embeddings, a unique approach not found in pure vector databases. --- ## 3. MEMORY_GUIDE.md **File Path:** `docs/guides/MEMORY_GUIDE.md` **Description:** User guide for Mimir's external memory system. Explains how to use MCP tools for context offloading and associative recall. **Relevance:** Demonstrates user-facing capabilities for memory management, a key differentiator. **Key Sections:** - Context Offloading Workflow - Memory Node Operations - Graph Relationship Management - Semantic Search Usage - Best Practices **Summary:** Used to explain Mimir's memory management capabilities to potential users. Highlights ease-of-use compared to manual graph database management. --- ## 4. FILE_INDEXING_SYSTEM.md **File Path:** `docs/architecture/FILE_INDEXING_SYSTEM.md` **Description:** Documentation for automatic file indexing and RAG enrichment system. **Relevance:** Unique feature not found in standard vector databases. **Key Sections:** - Automatic File Watching - .gitignore Support - File → Node Indexing - RAG Enrichment Pipeline **Summary:** Referenced for integration challenges section. File indexing provides automatic RAG context without manual embedding generation. --- ## 5. KNOWLEDGE_GRAPH_GUIDE.md **File Path:** `docs/guides/knowledge-graph.md` **Description:** Guide to building associative memory networks using Mimir's graph capabilities. **Relevance:** Demonstrates graph-based memory retrieval advantages over flat vector search. **Key Sections:** - Graph Relationship Types - Multi-Hop Traversal - Associative Recall Patterns - Graph Algorithms Integration **Summary:** Used for performance benchmarks section. Shows how graph traversal complements vector search for complex queries. --- ## 6. DOCKER_DEPLOYMENT_GUIDE.md **File Path:** `docs/guides/DOCKER_DEPLOYMENT_GUIDE.md` **Description:** Docker deployment instructions for Mimir + Neo4j. **Relevance:** Deployment simplicity comparison with competitors. **Key Sections:** - docker-compose Configuration - Neo4j Setup - Volume Management - Environment Variables **Summary:** Referenced for integration challenges. Demonstrates self-hosting simplicity compared to complex Kubernetes deployments required by some competitors. --- ## 7. CONFIGURATION.md **File Path:** `docs/configuration/CONFIGURATION.md` **Description:** Setup instructions for integrating Mimir with VS Code, Cursor, and Claude Desktop. **Relevance:** MCP integration is a unique differentiator not available in competing products. **Key Sections:** - MCP Server Configuration - VS Code Settings - Cursor Integration - Claude Desktop Setup **Summary:** Highlighted in strategic recommendations for MCP ecosystem opportunity. Direct AI assistant integration is exclusive to Mimir. --- ## 8. NEO4J_MIGRATION_PLAN.md **File Path:** `docs/architecture/NEO4J_MIGRATION_PLAN.md` **Description:** Plan for migrating from in-memory storage to persistent Neo4j graph database. **Relevance:** Explains persistence layer architecture and Neo4j dependency. **Key Sections:** - In-Memory → Neo4j Migration - Graph Schema Design - Cypher Query Patterns - Performance Considerations **Summary:** Referenced for risks section regarding Neo4j dependency. Also used for architecture overview to explain persistence layer. --- ## 9. PARALLEL_EXECUTION_SUMMARY.md **File Path:** `docs/PARALLEL_EXECUTION_SUMMARY.md` **Description:** Documentation for parallel task execution in multi-agent workflows. **Relevance:** Multi-agent orchestration capability not found in vector databases. **Key Sections:** - Parallel Group Assignment - Dependency Resolution - Concurrent Worker Execution - QC Verification Patterns **Summary:** Used for strategic recommendations to highlight Mimir's multi-agent orchestration as a unique selling point. --- ## Usage Notes All documentation files listed above were **directly referenced during the competitive analysis**. Citations in the technical report and strategic recommendations link back to these sources to ensure traceability and accuracy. ### Documentation Quality Assessment - **Completeness:** 9/10 (comprehensive coverage of features) - **Accuracy:** 10/10 (all information verified against codebase) - **Currency:** 9/10 (updated as of November 2025) - **Accessibility:** 8/10 (some advanced topics require technical background) ### Recommended Documentation Additions Based on competitive analysis, the following documentation gaps were identified: 1. **Performance Tuning Guide:** Optimize Neo4j vector index for specific workloads 2. **Migration Guides:** Step-by-step migration from Pinecone, Weaviate, Milvus 3. **Scaling Architecture:** Patterns for horizontal scaling beyond single-node 4. **Security Hardening:** Production security best practices 5. **Backup & Disaster Recovery:** Data protection strategies --- **Document Generated:** November 9, 2025 **Source Orchestration:** orchestration-1762728704 **Total Documentation Files Referenced:** 9