wasurenagusa-mcp
Related Servers
Alternatives to wasurenagusa-mcp
No user-submitted related servers found.
Related Servers
- AlicenseBqualityCmaintenanceAn MCP server that gives AI assistants persistent memory across sessions. It stores project context, decisions, and progress in structured markdown files as well as a knowledge graph and sequential thinking for better memory storage.36291MIT
- AlicenseAqualityAmaintenanceA local MCP server that gives AI assistants a long-term memory by capturing sessions verbatim and surfacing relevant context automatically.15872MIT
- AlicenseNot gradedqualityDmaintenanceA local MCP memory server that gives AI assistants durable project memory across coding sessions, storing context, changes, and decisions.31MIT
- AlicenseNot gradedqualityDmaintenanceA self-hosted MCP server that provides AI assistants with a shared, persistent SQLite-backed memory for storing and retrieving project context, decisions, and discoveries. It enables cross-session continuity and team-wide knowledge sharing to keep AI coding tools aligned and informed.3MIT
- AlicenseNot gradedqualityCmaintenanceAn MCP server that gives AI coding assistants persistent memory across sessions with chain-based project tracking, tickets, and structured handoffs.GPL 3.0
- FlicenseNot gradedqualityDmaintenanceAn advanced MCP server that gives AI assistants persistent memory with machine-learning-powered semantic understanding, enabling branching memory, semantic search, and project analysis.-
TDQS
Scored across 10 tools
Most tools have distinct purposes, but there is some overlap between memory_get_context and memory_get_detail, as both retrieve memory information. However, memory_get_context focuses on config and dont categories specifically, while memory_get_detail retrieves full details for any memory entry, which helps differentiate them. The other tools like memory_search, memory_save, and task-related tools are clearly distinct in their functions.
The naming follows a consistent verb_noun pattern throughout, such as memory_delete, memory_get_context, and task_submit. All tools use snake_case, which is uniform. The only minor deviation is project_init, which fits the pattern but stands out slightly as it doesn't start with a memory or task prefix, though it's still consistent in structure.
With 10 tools, the count is well-scoped for the server's purpose, which appears to be memory management and task automation. This number allows for comprehensive coverage without being overwhelming, including operations for memory CRUD, context retrieval, and task lifecycle management, making it efficient for agents to handle.
The tool set provides good coverage for memory operations (save, search, get, delete, update) and task management (init, action list, status, submit), but there are minor gaps. For example, there's no tool for updating memory content beyond intensity, and task operations lack direct update or delete functions, though agents might work around this with existing tools like task_action_list for resolution.