coldstart
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- FlicenseNot gradedqualityBmaintenanceEnables AI coding agents to keep persistent, verifiable memory of a codebase, including the reasons behind code, prior rejected approaches, and invariants, anchored to the code and carried along as the code moves.-
- AlicenseAqualityAmaintenanceOne local memory every coding agent on your machine shares — Claude Code, Cursor, Claude Desktop, OpenCode. Answers from past sessions, commits, CLAUDE.md/AGENTS.md and ADRs with the exact source, and withholds work another agent has claimed so two agents don't rewrite the same thing.4381 PyPI1MIT
- AlicenseAqualityCmaintenanceGives AI coding agents persistent, evolving knowledge about a codebase, enabling them to store and retrieve observations about architecture, conventions, gotchas, and recent work context.1040 npm2MIT
- AlicenseNot gradedqualityCmaintenancePersistent shared memory for AI coding agents that turns a folder of markdown files into searchable memory across sessions, repos, and machines.5 npmFunctional Source , Version 1.1, MIT Future
- FlicenseNot gradedqualityAmaintenancePersistent memory for AI coding agents: local-first semantic search, dependency graphs, git history.1-
- AlicenseNot gradedqualityAmaintenanceA local-first memory for AI coding agents. AgentRecall turns the feedback and failures you run into while coding into reusable rules, then serves the right ones back — on the command line or directly to Claude Code over MCP. Everything stays on your machine: no cloud sync, no web UI, no API keys.9MIT
TDQS
Scored across 8 tools
Each tool has a distinct trigger and output: find is repo-wide discovery, gs is drill-down into a known file, kb_search is fuzzy concept lookup, kb_lookup is exact-path lookup before edits, and kb_write/status/repair/repair_aliases each own a separate notebook lifecycle concern. The superficially similar pairs (kb_search/kb_lookup and kb_repair/kb_repair_aliases) are explicitly contrasted in their descriptions.
The kb_* tools share a clean, predictable prefix and snake_case convention, and find is a readable imperative. gs is an opaque abbreviation that does not fit the pattern, but it is a single isolated exception rather than a systemic inconsistency.
Eight tools is well-scoped for a code-intelligence-plus-notebook server: two navigation/analysis tools and six notebook read/write/maintenance tools. Every tool addresses a concrete workflow step, and the count sits comfortably in the ideal 3-15 range.
The notebook surface is fully covered: create/read/update/delete via kb_write, fuzzy search, exact-path lookup, status, and two repair paths for notes that become unreachable or stale. find and gs cover discovery and structural drill-down, and the only omitted action (git publishing) is intentionally documented as human-only.