Enables multi-agent systems to share memories, synchronize knowledge, and collaborate by managing memory registration, sharing, and insight generation across agents.
Coordinate multi-developer workflows with shared AI contexts, enabling seamless team collaboration across roles like frontend, backend, and devops for Agile projects on the Gemini MCP server.
Store information in persistent memory for multi-agent collaboration, enabling key-value data storage with optional expiration and type categorization.
Provides a shared context layer for AI agent teams to improve token efficiency through context deduplication and incremental state sharing. It enables multiple agents to coordinate tasks, share real-time discoveries, and manage dependencies while significantly reducing redundant data transmission.
A knowledge graph memory server using SQLite to provide persistent, isolated contexts for organizing information into searchable categories like work and personal projects. It features unique ID-based operations and a token-efficient serialization format designed to optimize interactions with LLMs.
An MCP server that allows users to run and visualize systems models using the lethain:systems library, including capabilities to run model specifications and load systems documentation into the context window.