curriculum_sync_pull
AI agents invoke curriculum_sync_pull to trigger actions in Cluster Execution MCP Server. 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.
The tool name suggests a pull/sync operation for curriculum data across cluster nodes. Given the server context (distributed execution, SSH, cluster management) and sibling tool 'curriculum_sync_push', this likely triggers a remote synchronization operation across nodes, which falls under Execute. However, 'pull' could also be a read/fetch operation. Confidence is lowered due to empty description.
From the tool's definition Tool name 'curriculum_sync_pull' on a cluster execution server with sibling tools like 'cluster_bash', 'broadcast_to_cluster', and 'curriculum_sync_push'. Description is empty.
Attacks that exploit this kind of access
curriculum_sync_pull. It is categorised as a Execute tool in the Cluster Execution MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Cluster Execution MCP Server MCP server in PolicyLayer and add a rule for curriculum_sync_pull: 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 Cluster Execution MCP Server. Nothing to install.
curriculum_sync_pull 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 curriculum_sync_pull 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 curriculum_sync_pull. 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.
curriculum_sync_pull is provided by the Cluster Execution MCP Server MCP server (marc-shade/cluster-execution-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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