Venice MCP Server

Instructions

Implementation Reference

• src/tools/inference/index.ts:57-81 (handler)

  The handler function for venice_generate_image tool. It constructs the request body, calls the Venice AI /images/generations API, handles errors, decodes and saves b64_json image to ~/venice-images/, or returns URL, and formats response as MCP content.

  async ({ prompt, model, size, style_preset, negative_prompt }) => {
    const body: Record<string, unknown> = { model, prompt, size, n: 1, response_format: "b64_json" };
    if (style_preset) body.style_preset = style_preset;
    if (negative_prompt) body.negative_prompt = negative_prompt;
  
    const response = await veniceAPI("/images/generations", { method: "POST", body: JSON.stringify(body) });
    const data = await response.json() as ImageGenerationResponse;
    if (!response.ok) return { content: [{ type: "text" as const, text: `Error: ${data.error?.message || response.statusText}` }] };
  
    const img = data.data?.[0];
    if (img?.b64_json) {
      const outputDir = getImageOutputDir();
      const filename = `venice-${Date.now()}.png`;
      const filepath = join(outputDir, filename);
      writeFileSync(filepath, Buffer.from(img.b64_json, "base64"));
      return {
        content: [{
          type: "text" as const,
          text: JSON.stringify({ success: true, path: filepath }),
        }],
      };
    }
    if (img?.url) return { content: [{ type: "text" as const, text: JSON.stringify({ success: true, url: img.url }) }] };
    return { content: [{ type: "text" as const, text: JSON.stringify({ success: false, error: "No image data returned" }) }] };
  }

• src/tools/inference/index.ts:49-56 (schema)

  Input schema using Zod for the venice_generate_image tool parameters: prompt (string), model (string opt default 'fluently-xl'), size (string opt '1024x1024'), style_preset (opt), negative_prompt (opt).

  {
    prompt: z.string().describe("Text description of the image to generate"),
    model: z.string().optional().default("fluently-xl").describe("Image model (e.g., fluently-xl, flux-dev)"),
    size: z.string().optional().default("1024x1024").describe("Image size (e.g., 512x512, 1024x1024, 1792x1024)"),
    
    style_preset: z.string().optional().describe("Style preset name"),
    negative_prompt: z.string().optional().describe("What to avoid in the image"),
  },

• src/tools/inference/index.ts:46-82 (registration)

  Direct registration of the 'venice_generate_image' tool on the MCP server via server.tool(), specifying name, description, input schema, and execution handler.

  server.tool(
    "venice_generate_image",
    "Generate an image from a text prompt using Venice AI",
    {
      prompt: z.string().describe("Text description of the image to generate"),
      model: z.string().optional().default("fluently-xl").describe("Image model (e.g., fluently-xl, flux-dev)"),
      size: z.string().optional().default("1024x1024").describe("Image size (e.g., 512x512, 1024x1024, 1792x1024)"),
      
      style_preset: z.string().optional().describe("Style preset name"),
      negative_prompt: z.string().optional().describe("What to avoid in the image"),
    },
    async ({ prompt, model, size, style_preset, negative_prompt }) => {
      const body: Record<string, unknown> = { model, prompt, size, n: 1, response_format: "b64_json" };
      if (style_preset) body.style_preset = style_preset;
      if (negative_prompt) body.negative_prompt = negative_prompt;
  
      const response = await veniceAPI("/images/generations", { method: "POST", body: JSON.stringify(body) });
      const data = await response.json() as ImageGenerationResponse;
      if (!response.ok) return { content: [{ type: "text" as const, text: `Error: ${data.error?.message || response.statusText}` }] };
  
      const img = data.data?.[0];
      if (img?.b64_json) {
        const outputDir = getImageOutputDir();
        const filename = `venice-${Date.now()}.png`;
        const filepath = join(outputDir, filename);
        writeFileSync(filepath, Buffer.from(img.b64_json, "base64"));
        return {
          content: [{
            type: "text" as const,
            text: JSON.stringify({ success: true, path: filepath }),
          }],
        };
      }
      if (img?.url) return { content: [{ type: "text" as const, text: JSON.stringify({ success: true, url: img.url }) }] };
      return { content: [{ type: "text" as const, text: JSON.stringify({ success: false, error: "No image data returned" }) }] };
    }
  );

• src/index.ts:15-18 (registration)

  Top-level registration of tool groups in main server entrypoint; registerInferenceTools includes the venice_generate_image tool.

  // Register all tool categories
  registerInferenceTools(server);
  registerDiscoveryTools(server);
  registerAdminTools(server);

• src/tools/inference/index.ts:9-15 (helper)

  Helper function to get or create the local directory ~/venice-images/ for saving generated images.

  function getImageOutputDir(): string {
    const dir = join(homedir(), "venice-images");
    if (!existsSync(dir)) {
      mkdirSync(dir, { recursive: true });
    }
    return dir;
  }