Run Dataview DQL query and return results
AI agents invoke execute_dataview_query to trigger actions in Obsidian MCP Server. 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 is classified as Execute rather than Read because Dataview DQL is a Turing-complete-adjacent query language capable of complex data transformations and side effects depending on the query. An AI agent given this tool could construct queries that extract sensitive information at scale, perform expensive computations, or (in some contexts) trigger cascading vault operations.
From the tool's definition 'Run Dataview DQL query and return results' — tool executes a query language (Dataview DQL) which can read and process data from the vault in potentially complex ways.
Documented attack patterns abuse exactly the kind of access execute_dataview_query gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Obsidian MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for execute_dataview_query:
{
"version": "1",
"default": "deny",
"tools": {
"execute_dataview_query": {
"limits": [
{
"counter": "execute_dataview_query_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}execute_dataview_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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Run Dataview DQL query and return results. It is categorised as a Execute tool in the Obsidian MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Obsidian MCP Server MCP server in PolicyLayer and add a rule for execute_dataview_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 Obsidian MCP Server. Nothing to install.
execute_dataview_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_dataview_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_dataview_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_dataview_query is provided by the Obsidian MCP Server MCP server (kynlos/obsidian-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Obsidian MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
120 Obsidian MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.