Fix Memory MCP
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Alternatives to Fix Memory MCP
No user-submitted related servers found.
Related Servers
- AlicenseAqualityAmaintenanceLocal-first memory layer for AI coding agents — captures issues, attempts, fixes, and decisions, and warns at git commit before you repeat a mistake.17822 PyPI876MIT
- FlicenseNot gradedqualityBmaintenancePersistent memory for AI coding agents: local-first semantic search, dependency graphs, git history.1-
- AlicenseNot gradedqualityAmaintenanceA persistent, local memory layer for AI coding agents that remembers decisions, bugs, and rules across sessions with three core MCP verbs (recall, remember, search).Apache 2.0
- AlicenseBqualityBmaintenancePersistent memory for AI coding agents, storing learned architecture decisions, patterns, and bug fixes in a local SQLite database with full-text search, enabling agents to recall information across sessions.6296 npm1MIT
- AlicenseAqualityBmaintenanceLocal-first memory for AI coding agents using SQLite, enabling persistent recall of decisions, lessons, and project context without cloud or API keys.10132 PyPI288Apache 2.0
- AlicenseAqualityCmaintenanceEnables AI coding assistants to share persistent local memory across sessions and agents, so rules, mandatory specs, verified code snippets, and past mistakes are automatically surfaced before code is generated. It also lets agents log repeated failures as recurrence-counted 'vaccines', preventing the same errors from recurring across Claude, VS Code agents, and local LLMs.72MIT
TDQS
Scored across 3 tools
The tools target distinct aspects: context assembly, general memory management, and lifecycle maintenance. However, manage_memory and maintain_memory_lifecycle could be confused due to overlapping scope, though descriptions help separate them.
All tool names follow a consistent verb_noun pattern using snake_case (assemble_context, manage_memory, maintain_memory_lifecycle), making the naming predictable and uniform.
With only 3 tools, the server is well-scoped and concise, covering context assembly, memory management, and lifecycle operations without unnecessary bloat.
The toolset covers the core memory lifecycle: assembling context, managing memory, and performing maintenance/recovery. Minor gaps like explicit search or list operations may exist, but manage_memory likely encompasses them.