get_data
AI agents call get_data to retrieve information from MoSPI MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The tool retrieves or queries statistical data from a government repository—a classic read operation with no side effects. Even with an empty description, the naming convention and peer tools (all read-only accessors) strongly suggest this is a data retrieval function.
From the tool's definition Tool name 'get_data' combined with server context describing 'access to Indian government statistics' and sibling tools 'get_indicators', 'get_metadata', 'list_datasets' all indicate retrieval operations.
Attacks that exploit this kind of access
get_data. It is categorised as a Read tool in the MoSPI MCP Server MCP Server, which means it retrieves data without modifying state.
Register the MoSPI MCP Server MCP server in PolicyLayer and add a rule for get_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 MoSPI MCP Server. Nothing to install.
get_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_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_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_data is provided by the MoSPI MCP Server MCP server (nso-india/esankhyiki-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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