register_email
Store an email address the user explicitly typed and submitted on the tier-picker onboarding screen (the
This record as markdown: /tools/ai-featureboard-featureboard/register-email.md
What register_email does on FeatureBoard
AI agents use register_email to create or update resources in FeatureBoard, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your FeatureBoard environment.
Why register_email is rated Medium
Storing an email address is a reversible write operation with minimal blast radius. It does not execute code, delete data, move money, or trigger external operations with unpredictable effects. The severity is low because email storage in an onboarding context is routine and low-risk, even if misused by an AI agent.
From the tool's definition Tool description indicates it 'Store[s] an email address' which is a data creation/modification operation. The description is incomplete (ends with '(the') but the core action is clearly writing/storing user-submitted data.
Attacks that exploit this kind of access
The rule that runs register_email safely
PolicyLayer is an MCP gateway: it sits between your AI agents and FeatureBoard, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For register_email, this is the rule to start with:
register_email stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect FeatureBoard, apply this rule, and every register_email call is checked against it from then on.
Questions about register_email
Store an email address the user explicitly typed and submitted on the tier-picker onboarding screen (the. It is categorised as a Write tool in the FeatureBoard MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the FeatureBoard MCP server in PolicyLayer and add a rule for register_email: 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 FeatureBoard. Nothing to install.
register_email 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 register_email 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 register_email. 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.
register_email is provided by the FeatureBoard MCP server (https://github.com/valentil/featureboard-mcp/releases/download/v0.7/featureboard.plugin). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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