agentbrush_edit_mask_result
Block until the mask editor session reaches "completed" (the user accepted a result), then download and save the edited image. Pair with agentbrush_edit_mask_open. Blocks for up to 30 minutes (matching the signed editor URL lifetime); returns immediately when the user accepts. session_id is the U...
This record as markdown: /tools/dev-agentbrush-mcp-server/agentbrush-edit-mask-result.md
What agentbrush_edit_mask_result does on Mcp Server
AI agents use agentbrush_edit_mask_result to create or update resources in Mcp Server, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Mcp Server environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
image_path | string | — | Optional absolute path of the original source image. When provided, the accepted result is saved alongside it; otherwise the file lands in the current working d |
session_id | string | Yes | Session ID returned by agentbrush_edit_mask_open (UUID v4). |
Parameters from the server's own tool schema.
Why agentbrush_edit_mask_result is rated Medium
This tool persists data (edited images) to storage, which is a Write operation. The severity is medium rather than high because the write is of user-generated image content (not system-critical data) and the operation is reversible. The confidence is 0.85 rather than higher because the description doesn't explicitly detail file path validation or potential for path traversal, but the write intent is clear.
From the tool's definition Tool downloads and saves an edited image to the file system: 'download and save the edited image' and 'the result is saved alongside it' or 'in the current working directory'. This creates or modifies files on disk.
Attacks that exploit this kind of access
The rule that runs agentbrush_edit_mask_result safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Mcp Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For agentbrush_edit_mask_result, this is the rule to start with:
agentbrush_edit_mask_result stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Mcp Server, apply this rule, and every agentbrush_edit_mask_result call is checked against it from then on.
Questions about agentbrush_edit_mask_result
Block until the mask editor session reaches "completed" (the user accepted a result), then download and save the edited image. Pair with agentbrush_edit_mask_open. Blocks for up to 30 minutes (matching the signed editor URL lifetime); returns immediately when the user accepts. session_id is the UUID returned by agentbrush_edit_mask_open. image_path is optional. Pass the same path you handed to _open so the result is saved alongside it; otherwise the saved file lands in the current working directory. It is categorised as a Write tool in the Mcp Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
agentbrush_edit_mask_result accepts 2 parameters: image_path, session_id. Required: session_id. The full parameter table on this page comes from the server's own tool schema.
Register the Mcp Server MCP server in PolicyLayer and add a rule for agentbrush_edit_mask_result: 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 Mcp Server. Nothing to install.
agentbrush_edit_mask_result is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the agentbrush_edit_mask_result 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 agentbrush_edit_mask_result. 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.
agentbrush_edit_mask_result is provided by the Mcp Server MCP server (@agentbrush/mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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