MCP For Claude Marketplace
Agent Workflow Cost Calculator

Agent Workflow Cost Calculator MCP Connector for Claude

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Calculate the exact financial footprint of multi-agent AI workflows.

3 tools Official Updated Oct 1, 2026 Official Vinkius Partner
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This MCP server provides precise financial analysis for multi-agent AI orchestrations. It allows AI agents to calculate the total cost of a workflow by analyzing token usage, model pricing, and execution frequency. Use calculate_workflow_economics to get a full breakdown of costs per step, total workflow cost, and optimization opportunities. You can also use identify_cost_drivers to find which agents are driving expenses or compare_model_alternatives to simulate how switching models affects your budget.

cost-analysisai-economicsworkflow-optimizationtoken-usagemulti-agent

3 tools expose this connector's capabilities to your AI agent.

calculate_workflow_economics

Calculates the complete financial breakdown of a multi-agent workflow

compare_model_alternatives

Evaluates how the total workflow cost would change if the most expensive agent was switched to a different model

identify_cost_drivers

Pinpoints which specific agents or models are disproportionately driving the total workflow cost

See how to talk to your AI agent using Agent Workflow Cost Calculator.

Calculate the economics for a workflow with two steps: 'Researcher' using GPT-4o (10k input, 2k output, 5 calls) and 'Writer' using Claude 3.5 Sonnet (5k input, 5k output, 1 call). GPT-4o costs $5/1m input and $15/1m output. Claude 3.5 Sonnet costs $3/1m input and $15/1m output.

The total workflow cost is $0.95. The Researcher step costs $0.40 per call, and the Writer step costs $0.12 per call. The most expensive agent is Researcher.

Which agent is the primary cost driver in my workflow?

The primary cost driver is the 'Data Extractor' agent, which accounts for 75% of the total workflow cost.

What happens if I switch the 'Summarizer' from GPT-4 to a cheaper model?

Switching the Summarizer to the alternative model will reduce the total workflow cost by 15%.

The tool calculates cost per step by summing the input and output token costs based on the provided model pricing, then multiplies this by the number of expected calls to find the total workflow cost.

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