Mark a message as read
AI agents use messages.mark_read to create or update resources in MCP Fullstack — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your MCP Fullstack environment.
Marking a message as read modifies the read/unread state of a message. This is a reversible write operation (it could be marked unread again). It does not delete, execute code, or involve financial transactions. Blast radius is very low as misuse would only affect message read status.
From the tool's definition Mark a message as read
Attacks that exploit this kind of access
Mark a message as read. It is categorised as a Write tool in the MCP Fullstack MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the MCP Fullstack MCP server in PolicyLayer and add a rule for messages.mark_read: 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 MCP Fullstack. Nothing to install.
messages.mark_read 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 messages.mark_read 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 messages.mark_read. 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.
messages.mark_read is provided by the MCP Fullstack MCP server (jacobfv/mcp-fullstack). 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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