Get comprehensive dataflow status with health monitoring and performance metrics
AI agents call monitor-dataflow-status to retrieve information from Fabric-Analytics-MCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and queries the status, health, and performance information of a dataflow. It performs no modifications, deletions, or side effects—only data retrieval and observation. The use of 'monitor' and 'get' confirms it is a read-only operation. No write, execute, destructive, or financial operations are implied.
From the tool's definition Tool name 'monitor-dataflow-status' and description 'Get comprehensive dataflow status with health monitoring and performance metrics' indicate retrieval of monitoring data and metrics only.
Documented attack patterns abuse exactly the kind of access monitor-dataflow-status gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Fabric-Analytics-MCP, and nothing reaches the server without passing your rules. This is the rule we recommend for monitor-dataflow-status:
{
"version": "1",
"default": "deny",
"tools": {
"monitor-dataflow-status": {}
}
}monitor-dataflow-status is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Get comprehensive dataflow status with health monitoring and performance metrics. It is categorised as a Read tool in the Fabric-Analytics-MCP MCP Server, which means it retrieves data without modifying state.
Register the Fabric-Analytics- MCP server in PolicyLayer and add a rule for monitor-dataflow-status: 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 Fabric-Analytics-MCP. Nothing to install.
monitor-dataflow-status 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 monitor-dataflow-status 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 monitor-dataflow-status. 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.
monitor-dataflow-status is provided by the Fabric-Analytics- MCP server (santhoshravindran7/fabric-analytics-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 83 Fabric-Analytics-MCP tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
83 Fabric-Analytics-MCP tools catalogued and risk-classified — across an index of 42,500+ MCP servers.