lore-mcp
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- AlicenseAqualityAmaintenancePersistent, local-first graph memory for AI coding agents. Provides durable cross-session memory via a local SQLite knowledge graph with typed relationships.61MIT
- FlicenseAqualityDmaintenanceA persistent, cross-session knowledge base for AI agents that indexes session history into a searchable SQLite database with full-text search, enabling recall of past sessions, stored knowledge, and summaries.10-
- AlicenseNot gradedqualityDmaintenanceProvides AI agents with persistent, searchable memory using a knowledge graph stored in SQLite. Features semantic search, temporal awareness, and workflow-aware prompts for development projects.15 npmMIT
- AlicenseNot gradedqualityAmaintenancePersistent knowledge memory layer for AI agents. Hybrid semantic + full-text search with pgvector, code dependency graph with blast-radius impact analysis, and incremental indexing for 7 languages. In-process ONNX embeddings, no external API required.38 npm35MIT
- AlicenseNot gradedqualityCmaintenanceGives AI coding agents persistent memory by storing observations, decisions, and learnings in a local SQLite database with vector search, full-text search, and a rules engine.4MIT
- AlicenseNot gradedqualityAmaintenanceLocal-first, single-file, knowledge-graph memory layer for AI agents.1MIT
TDQS
Scored across 42 tools
Most tools are cleanly separated by domain prefixes and detailed descriptions, but mcp_index_scan and mcp_index_rebuild are effectively the same operation, and the many search-related tools (kb_search, search_local, search_corpora, search_transcripts, multi_search) require careful reading to avoid mis-selection.
The naming is largely consistent: snake_case verb_noun patterns with domain prefixes like kb_, investigation_, journal_, and mcp_index_. Minor inconsistencies exist, such as mcp_index_scan/mcp_index_rebuild being duplicate operations and backfill_query_embeddings not following the kb_backfill_embeddings prefix style, but the overall pattern is predictable.
42 tools is far too many for a single MCP server, even one spanning knowledge bases, investigations, journals, search, telemetry, and MCP indexing. The surface would be more usable split into smaller focused servers or consolidated into fewer higher-level tools.
The knowledge base has full CRUD plus ingestion and embedding workflows; investigations, journals, search, telemetry, and MCP indexing all cover their core lifecycles. Minor gaps like no explicit investigation or journal update operation are likely intentional given the append-oriented design, but they are still notable omissions.