Supermemory MCPofficial
A
licenseNot graded
qualityF
maintenanceA universal memory server that allows users to access their chat memories across different LLMs without requiring logins or payment.
1,719
MIT
Waggle-mcp
Related Servers
Alternatives to Waggle-mcp
- AlicenseNot gradedqualityDmaintenanceEnables AI assistants to build and query temporally-aware knowledge graphs from conversations and data. Supports adding episodes, searching entities and facts, and maintaining persistent memory across interactions.10Apache 2.0
Related Servers
- AlicenseNot gradedqualityCmaintenanceOpen-source MCP server that gives any LLM long-term memory using a knowledge graph and vector search hybrid. It stores entities, observations, and relationships, enabling semantic recall across sessions with automatic clustering and fail-loud infrastructure.50MIT
- AlicenseNot gradedqualityAmaintenanceA universal MCP server providing persistent, structured memory through a knowledge graph with graph storage, semantic vector search, and multi-hop traversal for AI agents and IDEs.1MIT
- AlicenseAqualityAmaintenanceCognitive memory for AI agents. Works with Claude Code, Cursor, Windsurf, and any MCP-compatible client.21122 PyPI24MIT
- AlicenseNot gradedqualityAmaintenanceA local MCP server that gives LLMs long-term memory by indexing code, infrastructure, logs, and docs into a queryable graph. It enables semantic and structural search, evidence-backed reasoning, and tracked plans that persist across sessions and teams.1Apache 2.0
- AlicenseAqualityDmaintenanceAn MCP server that gives LLMs structured, verifiable memory by storing facts in a knowledge graph and enabling logic-based reasoning through natural dialogue.143MIT
- FlicenseNot gradedqualityBmaintenanceA remote MCP server that gives Claude (and ChatGPT/Gemini) persistent read/write access to your own memory: books, games, projects, notes, and freeform facts.-
TDQS
A3.5/5.0
Scored across 41 tools
Disambiguation3/5
Several tools have overlapping purposes: query_graph, aggregate_graph, get_related, build_context, and prime_context all retrieve memory context, differing mainly in scope and compression. Similarly, export_graph_html, window_graph_viz, and export_markdown_vault all export visualizations, and commit/pull/diff/merge/grep/show/fsck/load_abhi_chunks form a file-management cluster that may confuse agents. However, many tools are distinct (store_node, store_edge, delete_node, resolve_conflict).
Naming Consistency3/5
Most tools use verb_noun snake_case (store_node, delete_node, list_conflicts, resolve_conflict), but there are deviations: 'pull', 'diff', 'merge', 'grep', 'show', 'fsck' are bare git-like verbs, and 'timeline' is a noun. The mixed conventions are readable but not fully consistent.
Tool Count2/5
41 tools is excessive for a memory-graph MCP server. While the domain is broad (graph CRUD, context windows, file import/export, file format utilities), many tools could be consolidated (e.g., multiple export variants, multiple retrieval modes, multiple .abhi file inspection commands). The count feels heavy and will overwhelm agents.
Completeness4/5
The tool surface covers the full memory lifecycle: create/read/update/delete nodes and edges, conflict detection/resolution, context window management, import/export, backup/restore, and diagnostics. Minor gaps exist (e.g., no explicit edge update tool, no batch delete except clear_*), but the domain is thoroughly covered.
Maintenance
ActivityActive
ResponsivenessResponsive