Long-term neocortex and collective memory system for AI coding assistants via MCP. Provides grounded brain operations including search, retrieval, storage, and workflow recommendation for local work context.
Four read-only tools with complete input schemas and descriptions. All tools have proper verb_noun naming (brain_search, brain_get, brain_list_by_date, brain_list_by_label). Descriptions are adequate (50-100 chars) but lack actionable context about when to use each tool vs. alternatives. Parameters are well-typed with descriptions, but lack enum constraints for answer_mode and match_all. Output schemas are not documented, LLMs cannot predict response structure. Tool annotations present (readOnlyHint, idempotentHint, openWorldHint) but error handling and recovery guidance missing.
Return a canonical note by its stable identifier.
List notes by source-conversation date using YYYY-MM-DD bounds.
List notes connected to one or more canonical labels.
Search prior knowledge and return source-grounded results.
Output schemas not documented. LLMs cannot predict response structure (fields, types, nesting). brain_search returns dict but structure is opaque.
answer_mode parameter accepts free-form string ('conservative' or 'exploration') but lacks enum constraint. LLMs may hallucinate invalid values.
No error handling guidance. Tools lack recovery hints (e.g., 'If note not found, try brain_search with keywords'). Agents cannot self-correct on failures.
Descriptions lack context about tool selection. No guidance on when to use brain_search vs brain_list_by_date vs brain_list_by_label. LLMs must guess.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | B | 78 | 2026-07-28+ | v2 |
Pagination parameters (limit, offset) present but no total_count or next_cursor returned. LLMs cannot determine if more results exist.