Embedded MCP tool servers are pairing with the SQLite-Graph extension to power memory in AgentML. The idea is to treat memory as a living graph that can trigger tools and absorb tool results, all inside a deterministic agent model [1].
With AgentML, agents are defined as state machines where each state, transition, and tool call is explicit and machine-verifiable [1].
Two concrete workflows to imagine:
Memory graph updates trigger MCP tool invocations, letting tools run in response to evolving memory and emit results back into the agent’s decision path [1].
Tool results attach to memory nodes, creating a traceable trail that links evidence, action, and memory state for debugging and cost tracking [1].
In practice, teams like Agentflare are using this MCP-driven approach to add observability and cost tracking around agent actions [1].
Bottom line: pairing the MCP tool servers with the SQLite-Graph memory graph could turn memory into an active partner for agents, not just a store of facts [1].
References
MIT-licensed SQLite-Graph extension for SQLite powering AgentML memory; seeks feedback from LLM orchestrators and embedded MCP tool servers.
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