The Memory Store Tool
Persist facts, preferences, and outcomes to a governed memory store so an agent remembers what it learned — across turns, tasks, and days — instead of starting from zero every run.
Autonomous agents fail quietly
An agent that can act is only useful if it remembers, plans, and checks its own work. Without a cognitive core, agents forget context, skip steps, and state wrong answers with full confidence — and you find out too late.
No memory across runs
Agents start from zero every session, re-asking what they were already told.
Acting before thinking
Without an explicit plan, agents take the first path, not the right one.
Confident wrong answers
Nothing checks the output, so mistakes ship as if they were facts.
No accountability
When it goes wrong, there is no trace of why the agent did what it did.
Memory Store, without the risk
Capability
What it does
Give agents durable memory that survives the session.
it writes a fact, preference, or result to the agent’s persistent memory so it can be recalled in a later run.
- Namespaced, tagged memories
- Survives across sessions
- Per-tenant isolation
- Versioned and auditable
Assignable to any agent
How it works
Predictable, inspectable behavior
Designed to be reliable.
each memory is stored with a namespace, tags, and an owner, scoped per tenant and versioned, so writes are isolated, auditable, and safe to trust later.
Every call logged
Governance
Private, governed, on-premise
Runs inside your perimeter.
This tool runs inside your perimeter, scoped per user with full audit logging, so the agent’s reasoning, memory, and decisions stay private and accountable — never sent to a third-party service.
Per-tenant, logged
Parameters
The memory_store tool accepts these inputs when an agent calls it. Required inputs are flagged.
default: default Optional Logical grouping for the memory (e.g. per project or agent).
Where Memory Store pays back
Preference retention
Remember that a user always wants figures in EUR, without being told again.
Cross-session continuity
Carry findings from yesterday’s run into today’s.
Learned corrections
Store a correction so the agent never repeats the same mistake.
Team knowledge
Build a shared, governed memory an agent network can draw on.
Assigned to agents, orchestrated as networks
On VDF AI, an industry’s use cases map to agents, and you assign tools like this one to those agents. Compose multiple agents into a governed, on-premise network.
What changes after you assign it
Questions about the Memory Store tool
What is the Memory Store tool?
It writes a fact, preference, or result to the agent’s persistent memory so it can be recalled in a later run. Assigned to a VDF AI agent, it runs under role-based policy with full audit logging so the capability is safe to use in production.
How is a memory recalled later?
Pair it with the memory recall and memory search tools, which look up stored memories by key or by meaning within the same namespace and tenant.
Can memories expire?
Yes. Set ttl_days to have a memory expire automatically, or omit it to keep the memory until explicitly deleted.
Does it run on-premise?
Yes. Like every VDF AI tool, it can run on-premise or in your sovereign cloud, scoped per user and audit-logged, so your data never leaves your perimeter.
How do agents use it?
You assign the tool to an agent under a role-based policy; the agent calls it as one step in a task, and several agents and tools can be orchestrated together as a governed VDF AI Network.
Tools that work well alongside this one
Where this tool delivers value
Put Memory Store to work
See the Memory Store tool assigned to an agent and orchestrated in a governed, on-premise network.