Build histogram from input image and region, calculate mean and standard deviation. Calculate the mean and standard deviation of the histogram. The histogram collects count of data in provided image into a set of predefined bins. 基于输入图像和区域，生成直方图，计算直方图的均值和标准差。 工具不需要通过其它工具设置参数，不需要传入ILHistogram的对象。 ...
AI agents call il_histogram_build_mean_std_dev to retrieve information from Leaper Vision Toolkit without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
binCount | integer | — | 将直方图分为若干个统计区域，传入类型为int类型。推荐设置为总数据范围的因子，比如对一个灰度图，常用设置为 256 ，128，32 等。 |
imageUrl | string | — | 图片的url地址，通过这个地址获取到图片 |
lowerBound | integer | — | 统计数据范围的下限，传入类型为int类型。比如对一个 8 位灰度图，常用设置为 0。 |
regionJson | string | — | 指定的Roi区域。如果用户没有指定区域，请直接传入 "null"。 如果用户指定区域，传入一个序列化的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)。这两个属性的值可以从前处理的MCP工具的返回值中获取。LpvCl |
upperBound | integer | — | 统计数据范围的上限，传入类型为int类型。比如对一个 8 位灰度图，常用设置为 255。 |
Parameters from the server's own tool schema.
This tool performs read-only analysis on an image — it computes statistical metrics (mean and standard deviation) from a histogram and returns the results as JSON. No data is created, modified, deleted, or executed. Pure data retrieval/analysis operation.
From the tool's definition Build histogram from input image and region, calculate mean and standard deviation. Returns a serialized JSON with MeanValue and StdDevValue properties.
Attacks that exploit this kind of access
Build histogram from input image and region, calculate mean and standard deviation. Calculate the mean and standard deviation of the histogram. The histogram collects count of data in provided image into a set of predefined bins. 基于输入图像和区域，生成直方图，计算直方图的均值和标准差。 工具不需要通过其它工具设置参数，不需要传入ILHistogram的对象。 Returns a serialized JSON with MeanValue and StdDevValue properties. It is categorised as a Read tool in the Leaper Vision Toolkit MCP Server, which means it retrieves data without modifying state.
il_histogram_build_mean_std_dev accepts 5 parameters: binCount, imageUrl, lowerBound, regionJson, upperBound. 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_histogram_build_mean_std_dev: 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_histogram_build_mean_std_dev is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the il_histogram_build_mean_std_dev 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_histogram_build_mean_std_dev. 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_histogram_build_mean_std_dev 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.
Teams ship this data inside their own products. See what a licence covers →