federation_consensus
Propose a federated consensus operation across all active peers
This record as markdown: /tools/ruflo/federation-consensus.md
What federation_consensus does on Ruflo
AI agents invoke federation_consensus to trigger actions in Ruflo. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
Why federation_consensus is rated High
This tool triggers a distributed coordination operation across all active peer agents in the swarm. It initiates an external, multi-system operation whose effects depend on what consensus is being proposed and the state of the peer network.
From the tool's definition "Propose a federated consensus operation across all active peers"
Attacks that exploit this kind of access
The rule that runs federation_consensus 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 federation_consensus, this is the rule to start with:
federation_consensus stays usable, but rate-capped: a runaway agent can't fire it dozens of times 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 federation_consensus call is checked against it from then on.
Questions about federation_consensus
Propose a federated consensus operation across all active peers. It is categorised as a Execute tool in the Ruflo MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Ruflo MCP server in PolicyLayer and add a rule for federation_consensus: 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.
federation_consensus is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the federation_consensus 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 federation_consensus. 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.
federation_consensus 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.
Across the catalogue