Retrieve custom data
AI agents call get_custom_data to retrieve information from SDOF Knowledge Base without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool performs data retrieval with no side effects. It accesses stored custom data but does not create, modify, or delete anything. This is a classic Read category operation with minimal security risk.
From the tool's definition Tool name is 'get_custom_data' and description states 'Retrieve custom data'. The verb 'Retrieve' indicates a read-only operation that queries or fetches data without modification.
Attacks that exploit this kind of access
Retrieve custom data. It is categorised as a Read tool in the SDOF Knowledge Base MCP Server, which means it retrieves data without modifying state.
Register the SDOF Knowledge Base MCP server in PolicyLayer and add a rule for get_custom_data: 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 SDOF Knowledge Base. Nothing to install.
get_custom_data is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the get_custom_data 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 get_custom_data. 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.
get_custom_data is provided by the SDOF Knowledge Base MCP server (tgf-between-your-legs/sdof-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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