AI agents invoke obsidian_eval to trigger actions in Obsidian. 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 executes arbitrary JavaScript code within a live Obsidian instance, giving an AI agent full programmatic access to the application, the filesystem, and potentially the OS. Arbitrary code execution represents the highest level of Execute risk — a misuse could read/write/delete files, exfiltrate data, install malicious plugins, or pivot to the host system.
From the tool's definition "Runs arbitrary JavaScript inside the running Obsidian instance"
Attacks that exploit this kind of access
Runs arbitrary JavaScript inside the running Obsidian instance with access to the. It is categorised as a Execute tool in the Obsidian MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Obsidian MCP server in PolicyLayer and add a rule for obsidian_eval: 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. Nothing to install.
obsidian_eval 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 obsidian_eval 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 obsidian_eval. 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.
obsidian_eval is provided by the Obsidian MCP server (yuchi-chang/obsidian-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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