MemoryGuard
Related Servers
Alternatives to MemoryGuard
No user-submitted related servers found.
Related Servers
- FlicenseNot gradedqualityCmaintenanceA local-first MCP server that manages developer memory for coding agents, enabling shared project context, permissions, and audit trails across different agents.1-
- FlicenseNot gradedqualityDmaintenanceShared memory and orchestration for coding agents, enabling persistent knowledge, multi-agent coordination, and a canonical workflow across MCP-compatible AI clients.10110-
- AlicenseNot gradedqualityAmaintenanceEnables AI coding agents to share a local-first, versioned memory of decisions, conventions, tasks, conflicts, and handoffs over MCP and REST.2MIT
- AlicenseAqualityAmaintenanceMCP-native, local-first memory for coding agents that turns real sessions into reusable decisions, gotchas, and domain knowledge.176MIT
- AlicenseAqualityCmaintenanceA local-first MCP server that provides a shared Markdown-based memory for AI coding agents, enabling cross-agent context persistence via tools like memory_search and memory_capture.101MIT
- AlicenseNot gradedqualityCmaintenanceAn MCP-native, local-first memory server that gives AI agents persistent, structured memory across sessions and tools, enabling them to maintain identity and context without reconfiguration.3MIT
TDQS
Scored across 61 tools
Most core categories (memory CRUD, codegraph queries, rule merges) have distinct purposes, but several tools are nearly indistinguishable from their descriptions: history_search, history_timeline, history_read, and history_extract_preview are all described as 'V2-native read surface,' and the five knowledge_* tools offer no meaningful differentiation. With 61 tools, this ambiguity forces an agent to do a lot of guesswork.
All tools consistently use the memoryguard_ prefix and snake_case, which helps. However, the pattern flips between domain_action (memory_read, rule_undo, codegraph_query) and action_noun (list_sources, scan_summary, extract_memories, accept_candidates), and several names are bare nouns or adjectives (neuron_graph, codegraph_path, codegraph_affected, knowledge_book). The naming is readable but not predictably regular.
61 tools is an extreme count for a single MCP server, far exceeding the 'too many' threshold. Even with strong subdomain organization, an agent must navigate dozens of near-siblings across memory, rule merging, codegraph, enrichments, history, and knowledge, which creates a severe selection burden.
The governed memory, rule, enrichment, codegraph, and diagnostics lifecycles are extensively covered, including undo operations, merge previews, and pipeline status checks. Minor gaps exist, such as binding unbind being CLI/GUI-only and external MCP descriptors lacking update/delete tools, but core workflows are not dead-ended.