Executes a Kusto Query Language (KQL) query against the configured Azure Data Explorer database and returns the results as a list of dictionaries.
AI agents invoke execute_query to trigger actions in Adx. 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 allows an AI agent to run arbitrary KQL queries against a live Azure Data Explorer database. While the sibling tools (get_table_details, get_table_schema, list_tables, sample_table_data) are Read operations, this tool's ability to 'execute' queries means it can perform write, update, or delete operations depending on what KQL is submitted.
From the tool's definition Tool name is 'execute_query' and description states it 'Executes a Kusto Query Language (KQL) query against the configured Azure Data Explorer database'.
Documented attack patterns abuse exactly the kind of access execute_query gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Adx, and nothing reaches the server without passing your rules. This is the rule we recommend for execute_query:
{
"version": "1",
"default": "deny",
"tools": {
"execute_query": {
"limits": [
{
"counter": "execute_query_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}execute_query 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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Executes a Kusto Query Language (KQL) query against the configured Azure Data Explorer database and returns the results as a list of dictionaries. It is categorised as a Execute tool in the Adx MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Adx MCP server in PolicyLayer and add a rule for execute_query: 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 Adx. Nothing to install.
execute_query 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_query 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_query. 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_query is provided by the Adx MCP server (pab1it0/adx-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 5 Adx tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
5 Adx tools catalogued and risk-classified — across an index of 42,500+ MCP servers.