crazyrouter-mcp

Instructions

Implementation Reference

• src/index.ts:123-186 (handler)

  The "chat" tool registration and handler implementation using the Crazyrouter API to perform model completion.

  server.tool(
    "chat",
    "Send a message to any AI model via Crazyrouter. Supports 627+ models including GPT-5, Claude Opus 4.6, Gemini 3, DeepSeek R1, Llama 4, Qwen3, Grok 4, and more.",
    {
      model: z
        .string()
        .default(DEFAULT_CHAT_MODEL)
        .describe(
          `The AI model to use (default: ${DEFAULT_CHAT_MODEL}). Examples: gpt-5, claude-opus-4-6, gemini-3-pro, deepseek-r1, llama-4-scout, qwen3-235b, grok-4`
        ),
      messages: z
        .array(
          z.object({
            role: z
              .enum(["system", "user", "assistant"])
              .describe("The role of the message sender"),
            content: z.string().describe("The message content"),
          })
        )
        .describe("Array of chat messages with role and content"),
      temperature: z
        .number()
        .min(0)
        .max(2)
        .optional()
        .describe(
          "Sampling temperature (0-2). Lower = more deterministic, higher = more creative"
        ),
      max_tokens: z
        .number()
        .optional()
        .describe("Maximum number of tokens to generate"),
    },
    async ({ model, messages, temperature, max_tokens }) => {
      try {
        const body: Record<string, unknown> = { model, messages };
        if (temperature !== undefined) body.temperature = temperature;
        if (max_tokens !== undefined) body.max_tokens = max_tokens;
  
        const result = (await apiRequest("/chat/completions", {
          method: "POST",
          body,
        })) as {
          choices?: Array<{ message?: { content?: string; role?: string }; finish_reason?: string }>;
          usage?: { prompt_tokens?: number; completion_tokens?: number; total_tokens?: number };
          model?: string;
        };
  
        const content = result.choices?.[0]?.message?.content ?? "No response content";
        const usage = result.usage;
        const actualModel = result.model ?? model;
  
        let text = content;
        if (usage) {
          text += `\n\n---\n📊 Model: ${actualModel} | Tokens: ${usage.prompt_tokens ?? "?"}→${usage.completion_tokens ?? "?"} (${usage.total_tokens ?? "?"} total)`;
        }
  
        return { content: [{ type: "text" as const, text }] };
      } catch (error) {
        const message = error instanceof Error ? error.message : "Unknown error occurred";
        return { content: [{ type: "text" as const, text: `Error: ${message}` }], isError: true };
      }
    }
  );