Slipstream - Built by Vektor Memory - a persistent multi-layered memory architecture. 4-layer associative graph memory (MAGMA) with autonomous REM cycle, CLI, DXT-MCP Cloak Tools.
Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.
Smart memory for AI agents. Solves the Karpathy problem: memories decay, topics are frequency-weighted, one-time questions don't become obsessions. 7 tools. Zero deps.
Two-layer memory for AI agents. Episodes compress into identity.
The only MCP memory server with an immune system. Patterns earn permanence through evidence, false knowledge gets caught and demoted, and stale information fades — so your agent's memory gets smarter over time, not just bigger.
Zero dependencies. 5 tools. Works with any MCP client.
Memory for AI agents that can't hallucinate — answers only from stored facts with a
citation, or honestly abstains. Provable forgetting (GDPR), valid-time, Merkle
proofs, deterministic. MCP server, CPU-only, zero dependencies.
Enables AI agents to record and rank learnings, facts, and methods through a collaborative voting framework. It provides tools for agents to surface the most useful information across sessions using persistent memory storage.
Enables Claude to use Google Gemini as a secondary AI through MCP for large-scale codebase analysis and complex reasoning tasks. Supports both Gemini Flash and Pro models with specialized functions for general queries and comprehensive code analysis.
Persistent memory and handoff intelligence layer for MCP agents. Most memory servers retrieve text — Memory Nexus compounds operational context, learning from usage and progressively synthesizing observations into higher-order intelligence across sessions and tools.
Provides persistent memory for AgentChat agents with swim-lane summarization and self-evolving persona, enabling context management and persona mining across conversations.
A local, persistent memory system for AI coding assistants that stores decisions, patterns, and session context via MCP tools. It enables cross-session memory management using SQLite and optional vector search without external dependencies or cloud storage.
Persistent memory for AI coding agents that stores and recalls preferences, decisions, and conventions via semantic similarity, with zero cloud dependencies and plug-and-play MCP integration for Claude Code.
Provides persistent memory storage for AI agents with full-text search, tagging, and importance levels, enabling agents to store and retrieve memories efficiently.
Provides long-term memory for AI agents with per-user scoped recall, ranking by relevance, recency, and importance, consolidation of repeated events, and automatic forgetting.
Provides persistent cognitive memory for AI agents and robots with no LLM in the loop, using algorithms for storage, recall, and forgetting; supports MCP, HTTP, and ROS2.