robo-cortex
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- AlicenseNot gradedqualityDmaintenanceProvides a memory layer for AI coding agents with Git-powered version control, enabling automatic tracking of prompts, context, and code diffs.194MIT

Doclea MCPofficial
AlicenseNot gradedqualityCmaintenanceProvides persistent memory for AI coding assistants, storing and retrieving architectural decisions, patterns, and solutions across sessions using semantic search, while also offering git integration for commit messages and code expertise mapping.MIT- AlicenseAqualityBmaintenanceEnables AI coding agents to persist atomic, token-budgeted facts across sessions via SQLite-backed full-text search, automatically superseding outdated entries and flagging memories as stale when Git webhooks detect changes to anchored repo files.11AGPL 3.0
- AlicenseAqualityBmaintenanceA lightweight, Git-backed permanent memory for AI agents.323 PyPI60MIT
- AlicenseNot gradedqualityBmaintenanceProvides AI coding agents with a persistent memory layer to save, recall, update, and track memories across sessions and repositories using hybrid semantic search.5MIT
- AlicenseNot gradedqualityBmaintenancePersistent memory for AI coding agents that knows when it has gone stale.3MIT
TDQS
Scored across 9 tools
Each tool maps to a distinct action in the memory lifecycle: create (record_memory), read single (get_memory), read bulk (retrieve_context vs search_memory), mutate links (link_memories), transition state (change_status), add/re-verify evidence (attach_evidence vs verify_evidence), and proactive diff analysis (list_affected). The descriptions explicitly police the risky boundaries — search_memory states it is not the tool for building context, list_affected contrasts itself against both read paths, and link_memories vs change_status/supersedes_link_to is called out directly. The `scope` parameter's differing semantics per tool (disambiguator vs filter) are also documented rather than left implicit.
All nine tools follow a strict snake_case verb_noun pattern (attach_evidence, get_memory, link_memories, change_status, record_memory, list_affected, verify_evidence, retrieve_context, search_memory). Verbs are conventional and non-overlapping in meaning, so names alone convey the action. No camelCase or stylistic drift anywhere in the set.
Nine tools is well within the ideal band and each one earns its place: a create, three read paths with genuinely different purposes, two evidence operations, a link operation, a status transition, and a diff-driven risk report. No tool appears redundant or bolted on, and nothing essential to the described workflow is crammed into an overloaded multi-purpose tool.
The lifecycle is essentially closed: create, read, enrich with evidence, link, transition to terminal states (superseded/invalidated/abandoned/archived), proactively detect invalidation, and explicitly re-verify. Minor gaps remain — there is no way to edit a memory's statement text in place (only supersede and re-record), no unlink operation to undo an erroneous link_memories, and no enumeration/stats tool to browse the store without a query. These are workable around but would cost an agent extra steps in edge cases.