memory_migrate
Manually trigger migration from legacy JSON store to sql.js Use when native Read/Write is wrong because you need (a) cross-session retrieval by semantic similarity (vector embeddings) not by file path, (b) namespacing across projects without managing directory layout, or (c) the .swarm/memory.db ...
This record as markdown: /tools/ruflo/memory-migrate.md
What memory_migrate does on Ruflo
AI agents use memory_migrate to create or update resources in Ruflo, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Ruflo environment.
Why memory_migrate is rated Medium
This tool modifies the state of memory storage by migrating data from one format (JSON) to another (SQL database). While it does not delete the original data irreversibly (hence not Destructive), it performs a significant data transformation that alters the system's state. The operation could introduce bugs or data corruption if misused, affecting all downstream agent operations that depend on memory retrieval.
From the tool's definition Tool description explicitly states 'migration from legacy JSON store to sql.js' and mentions '.swarm/memory.db', indicating data transformation and modification.
Attacks that exploit this kind of access
The rule that runs memory_migrate safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Ruflo, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For memory_migrate, this is the rule to start with:
memory_migrate stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Ruflo, apply this rule, and every memory_migrate call is checked against it from then on.
Questions about memory_migrate
Manually trigger migration from legacy JSON store to sql.js Use when native Read/Write is wrong because you need (a) cross-session retrieval by semantic similarity (vector embeddings) not by file path, (b) namespacing across projects without managing directory layout, or (c) the .swarm/memory.db audit trail. For one-shot file I/O, native Read/Write is fine. It is categorised as a Write tool in the Ruflo MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Ruflo MCP server in PolicyLayer and add a rule for memory_migrate: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Ruflo. Nothing to install.
memory_migrate is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the memory_migrate rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for memory_migrate. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
memory_migrate is provided by the Ruflo MCP server (ruvnet/ruflo). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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