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Self-host shared memory, structured relays, and traceable evidence for AI runtimes.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "relaycore" yet — see the docs or source repo.
Please turn the key conclusions from this task into structured shared memory for later AI runtimes.
Structured, reusable memory entries.
Convert the following verbal request into machine-friendly structured commands and label the execution order.
A clear sequence of structured commands.
Please record the basis, conclusion, and key evidence of this AI decision for future traceability.
A decision record with an evidence trail.
Useful when multiple AI runtimes need to share the same context. It helps reduce information loss so later steps can continue from prior memory.
Useful for turning unstructured human requests into structured commands. This makes task handoff between AI tools or agents easier.
Useful when teams need auditability, traceability, or post-hoc review of AI outputs. It helps preserve decision evidence for later inspection.
It is a lightweight, self-hostable MCP server for shared memory, structured command relay, and traceable decision evidence across AI runtimes.
It is suitable for developers, DevOps users, and researchers who need shared context, structured task handoff, or traceable decision evidence across AI runtimes.
The provided information only says it is a self-hostable MCP server; installation and integration details are in the source repository.
Access and orchestrate a unified catalog of API tools via MCP.
Relay asynchronous Q&A between separate Claude Code instances without shared context.
Reliably relay jobs between agents and wake Claude when work completes.
Orchestrate AI team tasks with free models and Claude via MCP.
Use one MCP server for files, web search, screenshots, and planning workflows.
Connect local Codex agents to AgentRelay for orchestration and task management.