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count_tokens

Calculate token counts for text using specified Gemini models to manage input length and optimize API usage.

Instructions

Count tokens for a given text with a specific model

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesText to count tokens for
modelNoModel to use for token countinggemini-2.5-flash

Implementation Reference

  • The primary handler method for the 'count_tokens' tool. It extracts parameters, calls the underlying Gemini SDK's countTokens method, formats the token count result into an MCP response, and handles errors.
    private async countTokens(id: any, args: any): Promise<MCPResponse> { try { const model = args.model || 'gemini-2.5-flash'; const result = await this.genAI.models.countTokens({ model, contents: [ { parts: [ { text: args.text } ], role: 'user' } ] }); return { jsonrpc: '2.0', id, result: { content: [ { type: 'text', text: `Token count: ${result.totalTokens}` } ], metadata: { tokenCount: result.totalTokens, model } } }; } catch (error) { return { jsonrpc: '2.0', id, error: { code: -32603, message: error instanceof Error ? error.message : 'Internal error' } }; } }
  • Registers the 'count_tokens' tool in the list of available tools, defining its name, description, and input schema for MCP protocol.
    name: 'count_tokens', description: 'Count tokens for a given text with a specific model', inputSchema: { type: 'object', properties: { text: { type: 'string', description: 'Text to count tokens for' }, model: { type: 'string', description: 'Model to use for token counting', enum: Object.keys(GEMINI_MODELS), default: 'gemini-2.5-flash' } }, required: ['text'] } },
  • Zod schema definition for validating input parameters of the 'count_tokens' tool (text required, model optional).
    countTokens: z.object({ text: z.string().min(1, 'Text is required'), model: CommonSchemas.geminiModel.optional() }),

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