AI agents use session_save to create or update resources in Dobbe — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Dobbe environment.
This tool creates or modifies session context data that persists across commands, making it a Write operation. It is not Read (no retrieval described), Execute (no code/command execution), Destructive (data is saved, not deleted), or Financial.
From the tool's definition Tool name 'session_save' and description 'Save cross-command context for future use' indicate creation/modification of session state data.
Attacks that exploit this kind of access
Save cross-command context for future use. It is categorised as a Write tool in the Dobbe MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Dobbe MCP server in PolicyLayer and add a rule for session_save: 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 Dobbe. Nothing to install.
session_save 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 session_save 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 session_save. 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.
session_save is provided by the Dobbe MCP server (nareshnavinash/dobbe-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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