cortex
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- AlicenseNot gradedqualityBmaintenanceEnables AI coding agents to retrieve token-budgeted project context, search code symbols, look up definitions, and access project memory and cross-project learnings through local MCP tools. It reduces redundant exploration by supplying the smallest useful context from a deterministic, local-first index.MIT
- AlicenseNot gradedqualityDmaintenanceEnables AI coding agents to retrieve and manage code context with hybrid search, project memory, and observability via MCP tools.29MIT
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to locally search, query, and understand codebases with token-efficient context, dependency graphs, history, architecture diagrams, and metrics through MCP.15 npm3MIT
- FlicenseNot gradedqualityCmaintenanceProvides AI agents with a governed, three-layer project memory (guide, code facts, and knowledge) through namespaced MCP tools for code search, context compilation, impact analysis, and proposal-driven documentation updates.2 npm2-
- FlicenseBqualityBmaintenanceProvides AI coding agents with a hybrid cognitive memory engine that reduces token usage, prevents amnesia, detects repetitive error loops, and retrieves relevant code context through MCP.6-
- AlicenseNot gradedqualityAmaintenanceEnables AI coding agents to maintain persistent, cross-session memory of codebase architecture, naming conventions, and decisions through MCP tools. Eliminates repetitive project re-explanation by automatically injecting stored context into every session with local-first SQLite storage and optional team sharing capabilities.4MIT
TDQS
Scored across 10 tools
Most tools target clearly distinct resources and actions: the three memory tools (remember/recall/erase) split cleanly by CRUD verb, snapshots split by create/rewind, and symdex_lookup, sieve_compact, and shield_forecast each have unique purposes. The only mild overlap is between cortex_context_pack and cortex_prompt_lookup, which both operate on token/context handling and could be confused at a glance.
Every tool follows a strict cortex_<namespace>_<action> snake_case pattern (memory_remember, snapshot_create, sieve_compact, etc.). Namespace grouping is predictable and verbs are consistent in style across all ten tools.
Ten tools is well within the ideal 3-15 range and each maps to a distinct capability (memory, code lookup, log compaction, snapshots, safety forecast, context selection). No tool feels redundant or padded.
Memory offers full create/read/delete coverage and snapshots offer create/rewind, so the core lifecycle is present. Minor gaps remain (no snapshot list/prune or memory enumeration), but agents can work around these without dead ends.