hive-mind_memory
Access hive shared memory Use when native Task is wrong because you need queen-led collective intelligence — Byzantine-FT consensus, broadcast across many worker agents, shared memory with bounded conflict. For a single subagent, native Task is fine. Pair with swarm_init first to set topology.
This record as markdown: /tools/ruflo/hive-mind-memory.md
What hive-mind_memory does on Ruflo
AI agents call hive-mind_memory to retrieve information from Ruflo without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why hive-mind_memory is rated Low
The primary described action is 'access' (read) of shared memory, which leans Read. However, the mention of Byzantine-FT consensus, broadcasting to worker agents, and conflict resolution suggests this tool may also write to or modify shared memory state. The description is ambiguous about whether this is read-only or read-write.
From the tool's definition 'Access hive shared memory' — the tool is described as accessing (reading) shared memory; however, 'broadcast across many worker agents' and 'shared memory with bounded conflict' imply potential write/coordination side effects
Attacks that exploit this kind of access
The rule that runs hive-mind_memory 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 hive-mind_memory, this is the rule to start with:
hive-mind_memory is read-only, so it stays allowed. 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 hive-mind_memory call is checked against it from then on.
Questions about hive-mind_memory
Access hive shared memory Use when native Task is wrong because you need queen-led collective intelligence — Byzantine-FT consensus, broadcast across many worker agents, shared memory with bounded conflict. For a single subagent, native Task is fine. Pair with swarm_init first to set topology. It is categorised as a Read tool in the Ruflo MCP Server, which means it retrieves data without modifying state.
Register the Ruflo MCP server in PolicyLayer and add a rule for hive-mind_memory: 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.
hive-mind_memory is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the hive-mind_memory 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 hive-mind_memory. 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.
hive-mind_memory 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.
More on Ruflo, and thousands of servers like it.
This server
Across the catalogue