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Paste its GitHub repo and we list it after a quick review.
Turns a local Markdown or Obsidian vault into a governed knowledge substrate for AI agents to search, store, and retrieve durable memory.
$claude mcp add exomem -- uvx exomem
Provides a shared, editable memory layer that allows AI agents to recall decisions, preferences, and project context across different platforms.
$claude mcp add --transport http substrate-memory-plugins https://app.trysubstrate.co/mcp
Enables AI agents to perform multi-layered reasoning, maintain cross-session evolutionary memory, and orchestrate peer agents.
$claude mcp add mcp-cognitive-substrate -- uvx mcp-cognitive-substrate
Enables autonomous agents to coordinate through shared rooms, messaging, file exchange, and private per-agent memory stores.
$claude mcp add --transport http agent-coordination-substrate https://wiggle.network/mcp/
Provides a structured, four-layer memory substrate for long-horizon agents using write-gate admission and a hash-chained ledger.
Provides a shared memory substrate for AI agents that uses semantic retrieval, graph structures, and statistical feedback to improve context quality.
Provides a relational 3D grid memory substrate for AI agents to store and query structured data using the MTSV format.
Provides an epistemic memory substrate for AI agents to build structured, auditable knowledge graphs that persist across sessions.
Omnex is not a search tool. It is the memory substrate for the agentic era — the data layer that sits beneath AI agents, AI operating systems, and human-AI interaction. What exists today (file systems, folder hierarchies
The substrate is the asset; the model is an interchangeable client. Agent Context Substrate (ACS): model-independent memory for AI agents.
Next-Generation Distributed Multi-Agent Runtime & Swarm Substrate uniting Super-Memory, Cyclical Swarms, 24/7 Durable Daemons, Multimodal Streaming, VLA Safety Governors, and Benchmark Evaluators.