基于自定义核，对输入图像进行线性滤波，输出滤波结果的绝对值 。 Apply linear filtering on the given image using the custom kernel. kMat then report absolute value. 用户没有指定滤波相关参数时，不要调用设置参数的插件，传入的ILImageFilter 类的文件中已经设置了滤波相关的默认参数。 返回结构是一个序列化的json，其中： ResultImg属性是输出结果图像URL地址。
AI agents invoke il_image_filter_linear_filter_abs 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.
| Parameter | Type | Required | Description |
|---|---|---|---|
kMat | array | — | 滤波核的高度，传入类型为Array<double>类型，自定义核的数据，这是一组浮点数值 。 |
kWidth | integer | — | 滤波核的宽度，传入类型为int类型,自定义核的宽度，取值范围为 1 ~ 9999。 |
kHeight | integer | — | 滤波核的高度，传入类型为int类型，自定义核的高度，取值范围为 1 ~ 9999。 |
imageUrl | string | — | 图片的url地址，通过这个地址获取到图片 |
InputParameterFile | string | — | 指定的 ILImageFilter 类的文件地址，调用工具函数需要传入的参数文件名称。在调用此工具前要保证前处理中一定要有且仅有一次的 ILImageFilter 初始化工具调用。这个属性的值需要从前处理的MCP工具的返回值 InputParameterFile 字段中获取。 |
Parameters from the server's own tool schema.
This tool performs image processing computation (linear filtering with a custom kernel and absolute value transformation) on an input image and produces an output image URL. It executes a transformation operation rather than simply reading data or writing/modifying stored data in a reversible way. The 'custom kernel' aspect means the behavior depends on the arguments passed, making it Execute rather than a pure Read.
From the tool's definition Apply linear filtering on the given image using the custom kernel. kMat then report absolute value.
Attacks that exploit this kind of access
基于自定义核，对输入图像进行线性滤波，输出滤波结果的绝对值 。 Apply linear filtering on the given image using the custom kernel. kMat then report absolute value. 用户没有指定滤波相关参数时，不要调用设置参数的插件，传入的ILImageFilter 类的文件中已经设置了滤波相关的默认参数。 返回结构是一个序列化的json，其中： ResultImg属性是输出结果图像URL地址。. 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.
il_image_filter_linear_filter_abs accepts 5 parameters: kMat, kWidth, kHeight, imageUrl, InputParameterFile. The full parameter table on this page comes from the server's own tool schema.
Register the Leaper Vision Toolkit MCP server in PolicyLayer and add a rule for il_image_filter_linear_filter_abs: 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.
il_image_filter_linear_filter_abs 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 il_image_filter_linear_filter_abs 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 il_image_filter_linear_filter_abs. 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.
il_image_filter_linear_filter_abs 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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