This interface provide functionalities of edge extraction. 该接口类提供了图像边缘增强的功能。 To use this interface, you should create a LEdgeFilter object. 使用这个接口，需要创建一个 LEdgeFilter 对象。 Creates a new edge filter object for image edge enhancement. 创建一个图像边缘增强的功能调用的对象。 If other tools need the edge filter object, th...
AI agents invoke edge_filter_new to trigger actions in Leaper Vision Toolkit. 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.
The tool executes image processing operations (edge extraction/enhancement) by creating filter objects and invoking functions. This is Execute rather than Write because it triggers external image processing operations whose results depend on input arguments and parameters, making it an active computational operation rather than simple data creation.
From the tool's definition Creates a new edge filter object for image edge enhancement and returns serialized JSON with LpvClassName (function name) and InputParameterFile (parameter file name).
Attacks that exploit this kind of access
This interface provide functionalities of edge extraction. 该接口类提供了图像边缘增强的功能。 To use this interface, you should create a LEdgeFilter object. 使用这个接口，需要创建一个 LEdgeFilter 对象。 Creates a new edge filter object for image edge enhancement. 创建一个图像边缘增强的功能调用的对象。 If other tools need the edge filter object, they can use the current object JSON. 如果别的工具需要图像边缘增强的功能调用的对象，可以使用当前对象Json。 Returns a serialized JSON string with properties: LpvClassName (function name) and InputParameterFile (parameter file name). 返回结构是一个序列化的JSON字符串，属性包括：LpvClassName(调用工具函数的名称) 和 InputParameterFile(调用工具函数需要传入的参数文件名称)。 LpvClassName should be: ILEdgeFilter (edge enhancement function object). LpvClassName 表示图像边缘增强的功能调用的对象名称，目前名称应为：ILEdgeFilter (图像边缘增强的功能调用的对象); InputParameterFile represents the parameter file name for the edge filter object. InputParameterFile 表示图像边缘增强的功能调用的对象的参数文件名称。. It is categorised as a Execute tool in the Leaper Vision Toolkit MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Leaper Vision Toolkit MCP server in PolicyLayer and add a rule for edge_filter_new: 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 Leaper Vision Toolkit. Nothing to install.
edge_filter_new 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 edge_filter_new 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 edge_filter_new. 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.
edge_filter_new is provided by the Leaper Vision Toolkit MCP server (leaper-mcp/leaper-mcp-proxy). 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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