MCP server for MindBase — query and write to your wiki from Claude Desktop, Cursor, Windsurf, Cline, or any MCP-compatible AI client.
Four tools with basic descriptions and minimal input schemas. All tools are READ_ONLY and well-named with action verbs (search_, list_, get_, read_). Descriptions are present but brief (10-80 chars), below the 50-200 char LLM-optimized baseline. Input schemas exist but lack depth: most parameters have only type and description, no enums, ranges, or validation constraints. No output schemas documented. Error handling and recovery guidance absent. Tool composition is reasonable (each does one thing), but parameter descriptions are sparse and do not explain constraints, formats, or dependencies.
Get insights about the wiki graph structure, including node counts, connectivity, and community detection
List spaced repetition review cards, optionally filtered to due cards only
Read the full content of a wiki page by slug
Search the wiki for pages matching a query
Output schemas not documented. LLMs cannot plan downstream calls or extract required fields without knowing what each tool returns.
Descriptions are too brief (10-80 chars vs. 50-200 char baseline). 'Search the wiki for pages matching a query' lacks context on when to use this vs. read_wiki_page, what format results take, or pagination behavior.
Parameter descriptions lack constraint details. 'query' in search_wiki has no length limits, format hints, or examples. 'due_only' in list_review_cards has no explanation of what 'due' means (overdue? next 24h?). LLMs cannot validate inputs without explicit constraints.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | D | 54 | 2026-07-28+ | v2 |
No error handling or recovery guidance. If search_wiki returns no results, or read_wiki_page fails with 'page not found', the tool provides no actionable next steps for the LLM.
list_review_cards lacks pagination parameters (limit, offset, cursor). If a user has hundreds of review cards, returning all of them wastes tokens and risks context window exhaustion.