Execute a Spark Job Definition with execution data
AI agents invoke execute-spark-job-definition to trigger actions in Fabric-Analytics-MCP. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
This tool runs Spark jobs, which are arbitrary computational operations with side effects determined by job definition and input data. Misuse could consume significant compute resources, access sensitive data within Fabric, or cause downstream pipeline failures. Classified as Execute rather than Destructive because Spark job execution itself is reversible; the harm depends on what the job does.
From the tool's definition Tool name contains 'execute' and description states 'Execute a Spark Job Definition' — directly triggers external code execution (Spark job) with configurable parameters ('execution data').
Documented attack patterns abuse exactly the kind of access execute-spark-job-definition 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 execute-spark-job-definition:
{
"version": "1",
"default": "deny",
"tools": {
"execute-spark-job-definition": {
"limits": [
{
"counter": "execute-spark-job-definition_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}execute-spark-job-definition stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
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Execute a Spark Job Definition with execution data. It is categorised as a Execute tool in the Fabric-Analytics-MCP MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Fabric-Analytics- MCP server in PolicyLayer and add a rule for execute-spark-job-definition: 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.
execute-spark-job-definition is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the execute-spark-job-definition 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 execute-spark-job-definition. 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.
execute-spark-job-definition 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.