CometAPI MCP. Run any AI model from one place.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
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.
What your AI agents can do
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 text responses, create high-fidelity images from prompts, and convert audio files into written transcripts.
List every supported AI model (LLMs, image generators) and retrieve current pricing information for accurate cost planning.
Check real-time service status and track your account's total credit consumption to prevent unexpected billing issues.
Connect multiple disparate services (like text generation and image creation) into a single, coordinated process managed by your AI agent.
Ask AI about this MCP
Supported MCP Clients
OAuth 2.0 Compatible Gemini Waiting for input…
CometAPI MCP: 10 Tools Available
These tools allow you to manage everything from checking system status to generating images and monitoring the financial usage of your entire AI stack.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using CometAPI on Vinkius019dd0d4check api health
Verifies the current operating status of the connected API endpoint.
019dd0d4convert text to speech
Turns written text into an audible audio file format.
019dd0d4create ai chat completion
Generates a detailed, multi-turn text response using various large language models.
019dd0d4generate ai image
Creates original visual art based on a descriptive text prompt.
019dd0d4get api usage statistics
Retrieves the current account spending totals and usage metrics.
019dd0d4get current user
Pulls the profile information for the user who authenticated the connection.
019dd0d4get pricing information
Provides up-to-date cost structure details for specific AI models and services.
019dd0d4list available ai models
Lists every model type that the system can currently support or run.
019dd0d4list supported ai providers
Shows a list of all integrated companies providing AI capabilities.
019dd0d4transcribe audio to text
Converts spoken audio files back into editable, written text.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with CometAPI, then connect any of our 4,800+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,800+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by CometAPI. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
VINKIUS INFRASTRUCTURE
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on every call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 10 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Juggling 5 different provider dashboards for every new feature?
Right now, if you build an app that needs a voiceover, then an image, and then text analysis, you're forced to jump between five separate vendor consoles. You copy keys here, run the script there, check the billing dashboard over yonder. It’s slow, it’s messy, and it takes forever just to keep track of where your money is going.
With this MCP, you connect everything into one place. Your agent handles the handoffs between services—from converting text-to-speech to generating a visual asset—and you manage all that complexity from a single prompt. The result? You move faster and spend less time managing infrastructure.
Get full visibility into your AI workflow with CometAPI.
You don't just get the output; you get data on how it was generated. You can check which models were used and what the specific cost per call was, using tools like get_api_usage_statistics. This means knowing exactly what each step of your automation costs.
This oversight is huge. It lets you iterate confidently because if a complex workflow suddenly spikes in usage, you immediately know where to look and how much it’s costing.
What you can do with this MCP connector
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.
019dd0d4-fef7-7244-8f76-2c539a1efef3 
How CometAPI MCP Works
- 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.
The bottom line is that you manage many different AI systems through one single connection point.
Who Is CometAPI MCP For?
Any developer building an application or system that relies on more than a single AI vendor. You're the person who gets frustrated when they have to copy-paste keys and switch between 4 different provider dashboards just to run a prototype.
You build prototypes across multiple providers, using natural language commands instead of writing dozens of boilerplate API calls.
You automate the creation pipeline for marketing assets, generating text, images, and audio without leaving your core workspace.
You monitor the performance and costs across all AI features in a product, ensuring operational oversight through simple queries.
What Changes When You Connect
- 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.
Real-World 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.
The Tradeoffs
Relying on a single vendor's tools
Only building your agent using OpenAI's documentation because it was the first one you learned. This locks you into their pricing and model set.
→ Use this MCP to abstract away the provider layer entirely. You can swap out create_ai_chat_completion from Claude for one from Google without rewriting your core logic.
Ignoring cost visibility
Running complex, multi-step workflows like image generation and chat completion several times until the bill arrives. You only find out about the high costs later.
→ Always check get_api_usage_statistics before running a major test cycle. It gives you real-time budget control.
Confusing capability with availability
Assuming that because an AI model exists, your agent can use it without checking if the API is currently supported or stable.
→ Run check_api_health first. It confirms that the necessary endpoint is up and running before you try to send any data.
When It Fits, When It Doesn't
Use this MCP when your workflow requires combining different types of AI services—for instance, taking audio input, generating a corresponding image, and then writing documentation about it. If your process stays within one type of service (e.g., just text summarization), you might use a specialized client. However, if you need to monitor costs across multiple providers or combine media types, this MCP is essential because it provides the orchestration layer that makes cross-platform automation possible.
Common Questions About CometAPI MCP
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.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.