# CometAPI MCP MCP > CometAPI gives your AI client a single access point for hundreds of generative models and services. It lets you orchestrate complex workflows, generating images, writing text, converting speech, and monitoring the costs across multiple providers without switching dashboards. ## Overview - **Category:** developer-tools - **Price:** Free - **Tags:** model-aggregation, generative-ai, multimodal, chat-completion, image-generation, speech-to-text ## Description This connector turns your agent into a centralized intelligence layer. Instead of connecting to separate APIs for OpenAI, Anthropic, Midjourney, or Google, you connect once here. You can then build multimodal workflows that handle everything from turning a voice note into text, generating an image based on a prompt, and finally writing a detailed summary about it—all through one conversation with your AI client. It’s built for developers who need to prototype fast across many models or product leads who need full visibility. You can check which providers are supported and monitor your credit consumption in real time, letting you build complex automations without fear of overspending. Plus, because all these operations run through Vinkius, you get total visibility into every tool call, allowing you to track exactly what data moved where and how much it cost. This means nothing happens in the dark. ## Tools ### check_api_health Verifies the current operating status of the connected API endpoint. ### convert_text_to_speech Turns written text into an audible audio file format. ### create_ai_chat_completion Generates a detailed, multi-turn text response using various large language models. ### generate_ai_image Creates original visual art based on a descriptive text prompt. ### get_api_usage_statistics Retrieves the current account spending totals and usage metrics. ### get_current_user Pulls the profile information for the user who authenticated the connection. ### get_pricing_information Provides up-to-date cost structure details for specific AI models and services. ### list_available_ai_models Lists every model type that the system can currently support or run. ### list_supported_ai_providers Shows a list of all integrated companies providing AI capabilities. ### transcribe_audio_to_text Converts spoken audio files back into editable, written text. ## Prompt Examples **Prompt:** ``` Generate a summary of the latest AI trends using GPT-4. ``` **Response:** ``` AI summary generated! I've used GPT-4 to analyze recent breakthroughs. Highlights include advancements in multimodal reasoning and agentic workflows. Would you like a detailed breakdown for any specific trend? ``` **Prompt:** ``` Create a high-res image of a sustainable city using Midjourney. ``` **Response:** ``` Visual generation triggered! I've started creating your sustainable city image on Midjourney. You can access the result here: [image_url]. Shall I generate a matching logo design as well? ``` **Prompt:** ``` What is my current credit balance and average daily cost? ``` **Response:** ``` Scanning account... You have $25.50 in credits remaining. Your average daily cost is $1.20, giving you approximately 21 days of uptime at current levels. Need a list of supported providers? ``` ## Capabilities ### Orchestrate multi-modal output Generate text responses, create high-fidelity images from prompts, and convert audio files into written transcripts. ### Manage model selection and pricing List every supported AI model (LLMs, image generators) and retrieve current pricing information for accurate cost planning. ### Monitor usage and API health Check real-time service status and track your account's total credit consumption to prevent unexpected billing issues. ### Build agentic workflows Connect multiple disparate services (like text generation and image creation) into a single, coordinated process managed by your AI agent. ## Use Cases ### Generating a product mockup with a brand guide A marketing manager needs an asset. They ask their agent to use generate_ai_image to create the main visual, then use create_ai_chat_completion to write three catchy headlines for it, and finally use convert_text_to_speech to get a voiceover script—all without leaving their chat window. ### Analyzing competitor video content A business analyst feeds the agent an audio file. The agent uses transcribe_audio_to_text to convert it into text, then passes that transcript to create_ai_chat_completion to summarize key claims and identify weak points. ### Automating a technical blog post draft The developer needs a multi-part article. They use list_available_ai_models to select the best LLM, then run create_ai_chat_completion for the body text, generate_ai_image for the featured graphic, and finally convert_text_to_speech to prepare an accompanying podcast script. ### Verifying system capacity before launch A product lead needs cost estimates. They run get_api_usage_statistics, then use get_pricing_information to verify the per-token costs for multiple models, ensuring the feature stays within budget. ## Benefits - Stop managing dozens of API keys. Connect this MCP once, and your agent gains access to hundreds of models from multiple providers. - Build full media pipelines: Transcribe audio into text, use that text to generate an image prompt, then create the final visual asset—all in one chain. - Never guess your budget again. Use get_api_usage_statistics and get_pricing_information to track costs before you write a single line of code. - It handles all the complexity of model discovery. Use list_available_ai_models to know exactly what's possible without deep API research. - The orchestration is robust. Your agent acts like a dedicated model engineer, choosing the right tool for the job—whether it’s create_ai_chat_completion or generate_ai_image. ## How It Works The bottom line is that you manage many different AI systems through one single connection point. 1. First, you subscribe to this MCP and get an API Key from the CometAPI dashboard. 2. Next, you connect that key to your preferred AI client. Your agent now sees a unified list of hundreds of available models and services. 3. Finally, you prompt your agent with complex instructions—like 'Generate an image of X, then write a poem about it'—and the MCP coordinates all the necessary steps. ## Frequently Asked Questions **How do I check the cost of using generate_ai_image with CometAPI?** You first use get_pricing_information to see the current rates for image generation. Then, you can track your spending in real time by running get_api_usage_statistics. **Can I run a workflow that includes multiple AI models using create_ai_chat_completion?** Yes. This MCP is designed for orchestration. You can use the chat completion tool to chain together inputs and outputs from other tools, like passing text generated by one model into another. **What if my audio file is corrupted? Can I still transcribe it?** You should check the API health first using check_api_health. If the service reports issues, you know immediately that running transcribe_audio_to_text might fail. **Does this MCP let me see which AI providers are supported?** Absolutely. Use list_supported_ai_providers to get a full directory of companies whose models and APIs you can access right now. **What information does running `get_current_user` provide about my account?** It confirms your authenticated profile metadata. This tool lets you verify which user identity is making the API calls, ensuring proper tracking and attribution for every action taken by your agent. **Does `get_api_usage_statistics` help me monitor rate limits or throttling?** Yes. Beyond just costs, this tool provides a detailed history of your account usage. You can track call volume and see warnings if you're approaching any defined service rate limits. **If I need to generate an image, how do I find the right model using `list_available_ai_models`?** The list shows all supported models along with their core capabilities. You can filter this directory by modality—for instance, checking which models are specifically designated for high-fidelity image generation. **What does running `check_api_health` tell me about the connection reliability?** It performs a live diagnostic check on the entire system. A successful run confirms that all integrated services and endpoints are operational and ready for use by your AI client.