/**
* analyze_image MCP Tool
* Analyze images using xAI's vision-capable Grok models
*/
import { z } from "zod";
import { getXAIClient } from "../xai-client.js";
export const visionSchema = z.object({
image_url: z
.string()
.describe("URL of the image to analyze (or base64 data URL)"),
prompt: z
.string()
.optional()
.default("Describe this image in detail.")
.describe("Question or instruction about the image"),
detail: z
.enum(["low", "high", "auto"])
.optional()
.default("auto")
.describe("Image detail level for analysis"),
model: z
.string()
.optional()
.default("grok-2-vision-1212")
.describe("Vision model to use"),
});
export type VisionInput = z.infer<typeof visionSchema>;
export const visionTool = {
name: "analyze_image",
description:
"Analyze images using xAI's vision-capable Grok models. Describe, extract text, or answer questions about images.",
inputSchema: {
type: "object" as const,
properties: {
image_url: {
type: "string",
description: "URL of the image to analyze (or base64 data URL)",
},
prompt: {
type: "string",
description: "Question or instruction about the image",
default: "Describe this image in detail.",
},
detail: {
type: "string",
enum: ["low", "high", "auto"],
description: "Image detail level for analysis",
default: "auto",
},
model: {
type: "string",
description: "Vision model to use",
default: "grok-2-vision-1212",
},
},
required: ["image_url"],
},
};
export async function handleVision(input: VisionInput): Promise<string> {
const client = getXAIClient();
const validated = visionSchema.parse(input);
const analysis = await client.analyzeImage(
validated.image_url,
validated.prompt,
validated.detail
);
return JSON.stringify(
{
success: true,
analysis,
image_url: validated.image_url,
prompt: validated.prompt,
},
null,
2
);
}
