Plain Text Memory MCP
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- AlicenseNot gradedqualityDmaintenanceProvides persistent knowledge graph memory for AI agents, enabling them to store, recall, and query facts about people, projects, and relationships across sessions.MIT
- AlicenseNot gradedqualityCmaintenanceGives AI coding agents persistent, branch-aware memory and a dependency-tracked task graph by storing decisions, lessons, and tasks as plain JSON and Markdown committed directly into the repository. Agents can record and fuzzy-search past decisions, dump instant project context, and create, claim, complete, and query tasks whose completion automatically unblocks downstream work.MIT
- AlicenseNot gradedqualityAmaintenanceEnables AI assistants to store, query, and update persistent project knowledge as a local, Git-friendly knowledge graph, providing structured memory across sessions.9Apache 2.0

Oceanir Memoryofficial
FlicenseNot gradedqualityDmaintenanceProvides persistent long-term memory for AI coding agents by storing entities, relations, and observations across different sessions. It enables users to manage and query structured knowledge like coding preferences, project patterns, and technical solutions via a graph-based storage system.1-- AlicenseNot gradedqualityBmaintenanceProvides AI coding agents with git-native persistent memory and a dependency-aware task graph, letting them record and fuzzy-recall architectural decisions, lessons, and gotchas while creating, claiming, and completing tasks that auto-unblock downstream work. Stores everything as plain JSON and Markdown committed inside the repository, so context stays branch-aware, team-shared, and reviewable in pull requests.11 npmMIT
- AlicenseNot gradedqualityDmaintenanceProvides AI agents with persistent, searchable memory using a knowledge graph stored in SQLite. Features semantic search, temporal awareness, and workflow-aware prompts for development projects.4 npmMIT
TDQS
Scored across 14 tools
Every tool has a clearly distinct purpose, and descriptions explicitly cross-reference related tools (e.g., 'to add facts to an existing entity, see add_observations') to prevent misuse. Boundary cases like edit_observation vs. add_observations vs. merge_entities are well delineated.
Tool names follow a strict verb_noun pattern throughout (create_entities, add_observations, edit_observation, rename_entity, merge_entities, delete_entities, read_graph, search_nodes, open_nodes, etc.). The single exception, initialize_memory, is still verb_noun and clearly consistent with the rest.
With 14 tools covering entity CRUD, relation CRUD, observation CRUD, querying, merging, renaming, initialization, and export, the count is well-scoped. Each tool earns its place; no redundant or trivially thin operations.
The surface covers full lifecycle operations for entities, relations, and observations, plus graph-level read/search, taxonomy export, and memory file initialization. No obvious dead ends; the domain of a plain-text knowledge graph is fully served.