This record as markdown: /tools/7836246-claude-team-mcp/fix-bug.md
What fix_bug does on Claude Team MCP
AI agents invoke fix_bug to trigger actions in Claude Team MCP. 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 fix_bug is rated High
A bug-fix tool that invokes an AI QA expert to fix bugs will likely write or modify code, and may execute code to verify the fix. The most severe applicable category is Execute, as it triggers external AI operations and likely modifies source files. Severity is high because automated code changes by an AI agent can introduce new bugs, security vulnerabilities, or unintended behavior.
From the tool's definition fix_bug - 'QA 专家修复 Bug' (QA expert fixes bugs), implying automated code modification/execution
Attacks that exploit this kind of access
The rule that runs fix_bug safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Claude Team MCP, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For fix_bug, this is the rule to start with:
fix_bug 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 Claude Team MCP, apply this rule, and every fix_bug call is checked against it from then on.
Questions about fix_bug
让 QA 专家修复 Bug. It is categorised as a Execute tool in the Claude Team MCP MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Claude Team MCP server in PolicyLayer and add a rule for fix_bug: 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 Claude Team MCP. Nothing to install.
fix_bug 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 fix_bug 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 fix_bug. 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.
fix_bug is provided by the Claude Team MCP server (7836246/claude-team-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
More on Claude Team, and thousands of servers like it.
Across the catalogue