为复杂的功能开发、架构变更或大规模重构创建详细的实施计划。包括需求分析、步骤分解、风险评估和测试策略。
AI agents use code_plan to create or update resources in Unified MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Unified MCP Server environment.
An AI agent can call code_plan faster than any human can review — one bad instruction and it creates or modifies resources in Unified MCP Server by the hundred, each call as confident as the last.
Attacks that exploit this kind of access
为复杂的功能开发、架构变更或大规模重构创建详细的实施计划。包括需求分析、步骤分解、风险评估和测试策略。. It is categorised as a Write tool in the Unified MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Unified MCP Server MCP server in PolicyLayer and add a rule for code_plan: 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 Unified MCP Server. Nothing to install.
code_plan 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 code_plan 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 code_plan. 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.
code_plan is provided by the Unified MCP Server MCP server (qingyunyupan/ollama-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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