Cut AI Model Costs Without Losing Quality via MCP.
Your GPT-4o bill is $4,200/month and 60% of those calls could run on Groq for $0.003 , your agent finds the waste
Works with every AI agent you already use
…and any MCP-compatible client
Waiting for input…
Gemini How It Works
Your AI agent pulls your LLM usage data from Helicone , every request from the last 30 days with model, token count, cost, latency, and the request pattern.
It categorizes each request type: classification (short input, boolean/enum output), summarization (long input, short output), generation (variable input, long output), structured extraction (variable input, JSON output).
For classification and extraction tasks, the agent checks Groq's model catalog: Llama 3.1 70B on Groq runs at 300 tokens/second and costs $0.59/M input tokens.
GPT-4o costs $2.50/M input tokens. For a classification pipeline making 10,000 calls/day with 500 tokens average, that is $12.50/day on GPT-4o versus $2.95/day on Groq.
The agent writes the full analysis to Google Sheets: pipeline name, current model, current cost, recommended model, projected cost, savings, and risk assessment.
Tab two shows the 30-day projection: $4,200 current $1,680 optimized. $2,520/month in savings by routing the right calls to the right model.
Connector Orchestration: 3 Connectors, one intelligent agent
Connect Helicone, Groq and Google Sheets Connectors so your AI agent analyzes your LLM request logs from Helicone, identifies calls that can be routed to Groq's fast inference for 10-50x cost reduction, and builds a cost optimization report in Google Sheets. Teams spending $3,000-10,000/month on OpenAI who have never audited which calls actually need GPT-4o and which are classification tasks that Llama 3 handles fine get the answer in a spreadsheet.
Helicone Llm Observability
triggerAnalyzes LLM request patterns , model, tokens, cost, latency per call
query_requests query_costs query_latency query_prompts Groq
enrichmentProvides Groq model pricing and latency benchmarks for comparison
list_models get_model chat_completion Google Sheets
actionBuilds the cost optimization report with savings projections
append_sheet_values update_sheet_values get_spreadsheet create_spreadsheet Run This Automation Today
Connect Claude, ChatGPT, Cursor, or any AI agent to the Vinkius catalog and run this automation in minutes.
Build Your Own Connector
Convert any internal API into a Connector. 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 each call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Connect & Automate
The 3 servers this recipe uses are ready in the catalog. Connect them once, paste a prompt, and your AI runs the full workflow.
- Helicone Llm Observability, Groq & Google Sheets ready in the catalog right now
- Add more from 5,800+ servers whenever you need
- Connections are secured and compliant by default
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers and recipes added weekly
Superpowers you didn't know your AI had
The Vinkius catalog gives your agent access to 5,800+ Connectors and the intelligence to combine them. Imagine never logging into another dashboard. Your AI handles the work across all tools, in one conversation. That's what this connectivity layer was built for.
Cross-Platform Intelligence
Your agent doesn't just connect to tools. It understands the relationships between them. Data flows where it needs to go, automatically, with full context preserved across all platforms.
Contextual Reasoning
Each decision your agent makes considers the full picture. It reads CRM data, checks calendars, reviews conversation history, and acts on everything at once. Not step by step. All at once.
Productivity at Scale
What used to take 45 minutes across five different dashboards now takes one sentence. Your agent runs the entire workflow end to end while you focus on decisions that actually matter.
Zero-Config Reliability
No API keys to paste. No webhooks to configure. No YAML to debug. Connect your Connectors once, and your agent handles the rest. Each time, without intervention.
Made for
exactly this
Your AI agent taps into the entire Vinkius AI Connectors to handle these for you. You describe what you need. It does the rest.
AI engineering teams spending $3,000-10,000/month on OpenAI who have never audited which calls actually need a frontier model
CTOs who need a monthly LLM cost report with actionable optimization recommendations for the board
Platform teams evaluating Groq as a cost-reduction strategy for high-volume, low-complexity LLM workloads
Startups approaching their OpenAI spending cap who need to reduce costs without degrading product quality
Frequently Asked Questions About This Connector Orchestration
Which Connectors do I need for this workflow?
Three: Helicone, Groq and Google Sheets. Connect all three to your AI client before running any prompt from this page.
Does this work with Claude Desktop, Cursor or Windsurf?
Yes. Any AI client that supports the Model Context Protocol works , Claude Desktop, Cursor, Windsurf, Cline and others. Connect the Connectors and paste a prompt.
Do I need to already use Groq?
No. The agent uses Groq's model catalog and pricing for comparison. You do not need to route traffic through Groq until you decide to migrate. The report shows what you would save.
What if I use Anthropic instead of OpenAI?
Helicone tracks any LLM provider. The cost comparison works the same , the agent compares your current per-token cost with Groq's pricing regardless of which provider you use today.
Is my usage data secure?
Connectors authenticate through API keys. Helicone usage data stays in your account. The Google Sheet is in your Drive. Vinkius does not store your LLM usage data.
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Connectors used in this workflow
Helicone (LLM Observability)
Helicone MCP lets you monitor LLM usage, track costs, and manage prompts directly through your AI agent. It connects your Helicone account to your agent so you can see real-time data on request latency, spend, and user feedback without switching tabs. It's built for teams who need to see exactly what's happening with their AI infrastructure.
Groq
Groq MCP connects your AI agent to high-speed LPU-accelerated inference. It lets your agent handle text generation, audio transcription, and structured JSON outputs with sub-second latency. Use it to run models like Llama 3 and Mixtral at speeds that make standard inference feel sluggish.
Google Sheets
Google Sheets MCP lets you read, write, and manage spreadsheet data through your AI agent. Stop wasting time on manual data entry or complex formulas. Just tell your agent to pull specific ranges, add new rows, or create entire new sheets on the fly. It handles the tedious work of keeping your data organized so you can focus on making decisions.