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Interactive TCO Calculator

Calculate the Total Cost of Ownership (TCO) for deploying AI agents across different frameworks. Adjust the sliders to match your expected usage and see real-time cost comparisons.
Disclaimer: These calculations are estimates based on public pricing (as of 2025) and typical deployment patterns. Your actual costs may vary based on specific usage patterns, negotiated pricing, regional differences, and configuration choices.

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Usage Configuration

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Monthly Request Volume

10K1M requests/month10M

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Average Tokens per Request

1001,000 tokens/request10K

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Team Size (Developers)

13 developers20

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Workflow Complexity

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Deployment Region

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LLM Model Selection

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Cost Breakdown by Framework

The costs below are baseline estimates for 1M requests/month with Gemini 2.5 Flash. Use the sliders and dropdowns above to see dynamic calculations based on your specific configuration.

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MCP Server with LangGraph (Self-Hosted - Kubernetes)

Cost ComponentMonthly CostNotes
Infrastructure$350GKE cluster (4 pods, n2-standard-4)
LLM API Costs$420Gemini 2.5 Flash @ 0.30/0.30/2.50 per 1M tokens
Observability$50LangSmith + Prometheus + Grafana
Storage$20PostgreSQL + Redis (state/checkpoints)
Networking$15Load balancer + egress
DevOps Time$500~10 hours/month @ $50/hr (maintenance)
Total TCO$1,355/month$1.36 per 1,000 requests
💰 Cost Savings: $3,745/month vs LangGraph Cloud (73% cheaper)

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MCP Server with LangGraph (Cloud Run - Serverless)

Cost ComponentMonthly CostNotes
Cloud Run$600Serverless container hosting
LLM API Costs$420Gemini 2.5 Flash @ 0.30/0.30/2.50 per 1M tokens
Observability$50LangSmith + Cloud Monitoring
Storage$30Cloud SQL + Memorystore
Networking$25Cloud Load Balancer
DevOps Time$200~4 hours/month (less maintenance)
Total TCO$1,325/month$1.33 per 1,000 requests
💰 Cost Savings: $3,775/month vs LangGraph Cloud (74% cheaper)

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LangGraph Cloud (Managed Platform)

Cost ComponentMonthly CostNotes
Platform Fees$5,000$0.001/node × 5M node executions
Uptime Fees$100Always-on deployment
LLM API Costs$0Included in platform fees
Observability$0LangSmith included
Storage$0Included in platform
DevOps Time$0Fully managed
Total TCO$5,100/month$5.10 per 1,000 requests
⚠️ Trade-off: Zero DevOps effort, but 4x higher cost at scale

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OpenAI AgentKit (Platform)

Cost ComponentMonthly CostNotes
Platform Fees$0No separate AgentKit fee
GPT-5.1 API$1,6881B tokens @ 1.25/1.25/10 per 1M tokens
Web Search$50050K searches @ $10/1K calls
ChatKit Storage$20200 GB-days @ $0.10/GB-day
Observability$0Basic Evals included
DevOps Time$0Fully managed
Total TCO$2,208/month$2.21 per 1,000 requests
  • ❌ Vendor Lock-in: OpenAI models only, limited flexibility

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CrewAI (Self-Hosted)

Cost ComponentMonthly CostNotes
Infrastructure$200Single VM (n2-standard-2)
LLM API Costs$420Gemini 2.5 Flash @ 0.30/0.30/2.50 per 1M tokens
Observability$0Basic logging only
Storage$10Local SQLite (not production-ready)
Networking$5Minimal
DevOps Time$800~16 hours/month (manual setup)
Total TCO$1,435/month$1.44 per 1,000 requests
⚠️ Note: Low infrastructure cost, but high DevOps burden for production features

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Google ADK (Vertex AI Agent Engine)

Cost ComponentMonthly CostNotes
Vertex AI Agent Engine$1,500Platform fees
Gemini 2.5 Pro API$1,6881B tokens @ 1.25/1.25/10 per 1M tokens
Cloud Storage$30Agent state/artifacts
Networking$20VPC, load balancer
Observability$100Cloud Monitoring + Trace
DevOps Time$300~6 hours/month
Total TCO$3,638/month$3.64 per 1,000 requests
  • ⚠️ Trade-off: Good for GCP-native, but 2.5x more expensive than self-hosted MCP Server

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Cost Comparison Chart

Loading dynamic cost comparison chart…
Best Value: Calculating based on your configuration…

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TCO Factors Explained

Kubernetes (GKE/EKS/AKS):
  • Cluster management: $70-150/month
  • Node pools: $250-400/month (4 pods, n2-standard-4)
  • Load balancer: $15-30/month
  • Total: ~$350/month for 1M requests
Cloud Run (Serverless):
  • Pay-per-use: $0.40-2.00 per 1M requests
  • Always-on: Add ~$200/month for warm instances
  • Total: ~$600/month for 1M requests
Platform Fees (LangGraph Cloud, OpenAI):
  • Node executions: 0.001/node(5Mnodes=0.001/node (5M nodes = 5,000)
  • API markup: Often included but higher per-request cost
Model Selection Impact:
  • Gemini Flash: $0.075/1M tokens (cheapest)
  • Claude Haiku: $0.25/1M tokens
  • GPT-4o Mini: $0.15/1M tokens
  • GPT-4: $10-30/1M tokens (most expensive)
For 1M requests @ 1,000 tokens/request:
  • Gemini Flash: $75/month
  • GPT-4: $10,000/month (133x more expensive!)
Optimization: Use cheaper models for high-volume workloads, premium models for complex reasoning.
Self-Hosted (Kubernetes):
  • Initial setup: 20-40 hours (one-time)
  • Monthly maintenance: 8-12 hours
  • Troubleshooting: 2-5 hours
  • Total: ~10 hours/month @ 50−100/hr=50-100/hr = 500-1,000
Serverless (Cloud Run):
  • Initial setup: 4-8 hours
  • Monthly maintenance: 2-4 hours
  • Total: ~4 hours/month = $200-400
Managed Platforms:
  • Zero DevOps time (fully managed)
  • Trade-off: 5-10x higher platform fees
MCP Server (Dual Stack):
  • LangSmith: $0-50/month (usage-based)
  • Prometheus + Grafana: Self-hosted (free) or Cloud ($50-100/month)
  • Total: ~$50-100/month
Managed Platforms:
  • Included in platform fees
  • Limited customization
  • No infrastructure metrics (only LLM tracing)
Value: Self-hosted observability provides more visibility at lower cost.
Vendor Lock-in Opportunity Cost:
  • Switching costs if pricing changes
  • Negotiation leverage with multi-cloud
  • Value: Estimated $500-2,000/month in flexibility
Learning Curve:
  • Team onboarding time: 40-80 hours (one-time)
  • Training costs: $2,000-5,000 (one-time)
  • Amortized: ~$200-400/month over 12 months
Compliance/Audit:
  • SOC 2 audit: $20,000-50,000 (annual)
  • HIPAA readiness: $10,000-30,000 (one-time)
  • Amortized: ~$200-500/month

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Break-Even Analysis

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When Does Self-Hosting Pay Off?

  • Low Volume (< 100K/month)
  • Medium Volume (100K - 1M/month)
  • High Volume (> 1M/month)
Recommendation: Managed platform (LangGraph Cloud or OpenAI AgentKit)Why:
  • DevOps overhead dominates costs at low volume
  • Platform fees are low (< $500/month)
  • Time-to-market matters more than cost optimization
Example:
  • 50K requests/month
  • LangGraph Cloud: $250/month (platform fees)
  • MCP Server: $400/month (infrastructure + DevOps)
  • Winner: LangGraph Cloud (simpler, cheaper)

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3-Year TCO Projection

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Total Cost Over 3 Years (assuming 1M req/month growth)

FrameworkYear 1Year 2Year 33-Year Total
MCP Server (K8s)$12,000$18,000$24,000$54,000
MCP Server (Cloud Run)$12,000$18,000$24,000$54,000
LangGraph Cloud$61,000$122,000$183,000$366,000
OpenAI AgentKit$126,000$252,000$378,000$756,000
Google ADK$25,000$40,000$60,000$125,000
Savings: MCP Server saves $312,000 over 3 years vs LangGraph Cloud at scale.

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ROI Calculator

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Return on Investment for Self-Hosting

Scenario: Migrating from LangGraph Cloud to MCP Server (K8s) Initial Investment:
  • Setup time: 40 hours @ 100/hr=100/hr = 4,000
  • Training: $3,000
  • Total: $7,000 (one-time)
Monthly Savings:
  • Platform cost reduction: 5,100−5,100 - 1,010 = $4,090/month
Break-Even:
  • 7,000/7,000 / 4,090 = 1.7 months
12-Month ROI:
  • Savings: 4,090×12=4,090 × 12 = 49,080
  • Investment: $7,000
  • ROI: 601% ($42,080 profit)

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Cost Optimization Strategies

Choose Cheaper LLMs

Use Gemini Flash ($0.075/1M tokens) for 90% of requests, GPT-4 for complex reasoning only.Savings: 10-20x on LLM costs

Implement Caching

Cache common queries with Redis TTL.Savings: 30-50% reduction in LLM API calls

Batch Requests

Group multiple requests for parallel processing.Savings: 20% infrastructure efficiency gain

Use Spot Instances

Kubernetes node pools with spot/preemptible VMs.Savings: 60-80% on compute costs

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Frequently Asked Questions

Three reasons:
  1. No Platform Markup: You pay cloud costs directly (no 10x markup)
  2. Model Flexibility: Use cheaper LLMs (Gemini Flash vs GPT-4)
  3. Economies of Scale: Self-hosting benefits from volume (managed platforms charge per-request)
Trade-off: Requires DevOps expertise and maintenance time.
These estimates are based on:
  • Public pricing (GCP, AWS, Azure, LLM providers) as of 2025
  • Typical deployment patterns from real-world usage
  • Average assumptions (e.g., 1,000 tokens/request)
Your costs may vary based on:
  • Negotiated enterprise pricing
  • Regional pricing differences
  • Actual token usage (can be 100-10,000+ tokens/request)
  • Custom configurations and optimizations
Included in estimates but can vary significantly:
  • GCP: $0.12/GB (North America)
  • AWS: $0.09/GB (first 10 TB)
  • Azure: $0.087/GB (first 5 GB free)
For 1M requests:
  • Average response: 2 KB
  • Total egress: 2 GB = $0.18-0.24/month (negligible)
Exception: Large file transfers or streaming can significantly increase egress costs.
Strategies:
  1. Use Cloud Run instead of Kubernetes (4 hours vs 10 hours/month)
  2. Automate deployments with CI/CD (GitHub Actions, ArgoCD)
  3. Use Helm charts provided by MCP Server (pre-configured)
  4. Enable auto-scaling to reduce manual intervention
  5. Invest in monitoring to catch issues early
Result: Reduce maintenance to 2-4 hours/month after initial setup.

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Next Steps

Try MCP Server

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Deployment Guide

Deploy to Kubernetes

Multi-LLM Setup

Advanced cost reduction strategies

Framework Comparison

Full framework comparison