successful-tool
A tool that always succeeds (for comparison)
This record as markdown: /tools/frontmcp/successful-tool.md
What successful-tool does on Frontmcp
AI agents call successful-tool as a supporting operation in Frontmcp workflows.
Why successful-tool is rated Low
The description is vague and appears to be a test/demo tool used for comparison purposes. It provides no information about what the tool actually does — no data access, no writes, no execution of commands. Given the framework context (FrontMCP is a TypeScript MCP framework), this is likely a stub or example tool.
From the tool's definition A tool that always succeeds (for comparison)
Attacks that exploit this kind of access
The rule that runs successful-tool safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Frontmcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For successful-tool, this is the rule to start with:
successful-tool gets a rate cap, and everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Frontmcp, apply this rule, and every successful-tool call is checked against it from then on.
Questions about successful-tool
A tool that always succeeds (for comparison). It is categorised as a Other tool in the Frontmcp MCP Server, which means it performs auxiliary operations.
Register the Front MCP server in PolicyLayer and add a rule for successful-tool: 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 Frontmcp. Nothing to install.
successful-tool is a Other tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the successful-tool 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 successful-tool. 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.
successful-tool is provided by the Front MCP server (agentfront/frontmcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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