remove_edge
AI agents call remove_edge to permanently remove resources in Dify MCP — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
The tool name 'remove_edge' implies deletion of a workflow edge (connection between nodes). In the context of workflow DSL editing, removing an edge is likely irreversible without undo functionality.
From the tool's definition Tool name 'remove_edge' combined with sibling tools like 'add_edge', 'add_node' variants suggesting a graph/workflow editing context where removing an edge deletes a connection between nodes irreversibly.
Attacks that exploit this kind of access
remove_edge. It is categorised as a Destructive tool in the Dify MCP MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Dify MCP server in PolicyLayer and add a rule for remove_edge: 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 Dify MCP. Nothing to install.
remove_edge is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the remove_edge 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 remove_edge. 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.
remove_edge is provided by the Dify MCP server (taiki-kuraishi/dify-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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