Wuniq
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Related Servers
- FlicenseNot gradedqualityAmaintenanceGives AI coding agents direct, local-first read/write access to persistent memory — project decisions, preferences, error patterns, research, and cross-project guidelines — retrieved by semantic search backed by SQLite with no API keys or network calls. A companion server also exposes optional autonomous task-queue execution.-
- AlicenseAqualityAmaintenanceLocal-first memory layer for AI coding agents — captures issues, attempts, fixes, and decisions, and warns at git commit before you repeat a mistake.17810 PyPI872MIT
- AlicenseAqualityDmaintenanceLocal-first project memory for AI coding agents. Records failed attempts, fragile files, and decisions per repo, and warns the agent via hooks before it repeats a recorded mistake.60MIT
- FlicenseNot gradedqualityAmaintenanceProvides AI coding agents with a local-first persistent memory layer they can read and write during sessions, storing decisions, preferences, error patterns, and research per project or globally. Enables semantic and keyword search, formatted context recall, and cross-project guideline surfacing without API keys or cloud storage.-
- FlicenseNot gradedqualityAmaintenanceEnables AI coding agents to read and write persistent, local-first memory so project decisions, preferences, and cross-project guidelines survive across sessions and can be retrieved by semantic search. Optionally also exposes a task queue for autonomous execution that draws on the same stored context.-
- AlicenseAqualityAmaintenanceLocal, searchable project memory for AI coding agents. Markdown source of truth, MCP interface, safe structured updates315Apache 2.0
TDQS
Scored across 1 tool
The single 'run' tool is overloaded with many distinct commands (open, read, search, graph, new, edit, relation, sync, help), making it ambiguous what it does and when to use it versus native tools. Agents may struggle to determine the correct command or differentiate from other tools.
With only one tool named 'run', there is no pattern to evaluate. The name is overly generic and does not reflect any domain-specific convention.
A single tool for a knowledge engine that supports multiple diverse operations is far too few. Typically, such a domain would require separate tools for each operation (e.g., search, read, create) to avoid overloading and improve clarity.
While the tool claims to cover many actions, it is monolithic and may be incomplete for complex workflows. The description also defers 'ordinary project files' to native tools, creating potential gaps and reliance on external tools.