Compare on-demand compute, block/object storage, managed Postgres, egress & GPU pricing across AWS, Azure, GCP, and OCI, plus FinOps decision tools (RI/Savings Plan break-even, multi-cloud workload TCO, exit-cost migration analysis, and egress arbitrage). 25 tools.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.
We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag — we're steadily working through the catalog.
💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by Cloudprice MCP.
get_aws_priceLook up an EC2 instance type → vCPUs, memory, hourly + monthly USD (us-east-1)
get_azure_priceLook up an Azure VM size → vCPUs, memory, hourly + monthly USD (eastus)
get_gcp_priceLook up a GCP Compute Engine machine type → vCPUs, memory, hourly + monthly USD (us-east1)
compare_cloudsGiven a target spec (vCPUs + GB), return the cheapest matching SKU across **AWS / Azure / GCP / OCI**, sorted by monthly cost, with savings summary
compare_compute_inventoryBulk-compare a list of compute workloads (each with vCPUs / memory / quantity / hours / optional OS disk) across all 4 clouds. Returns per-row matches, per-cloud totals, cheapest cloud.
compare_storage_inventoryBulk-compare a list of block-storage volumes (each with capacity / disk type / quantity) across all 4 clouds.
The FinOps MCP server. Gives Claude, GitHub Copilot, Cursor, Windsurf, Cline, Continue, Zed — or any MCP-compatible AI — structured pricing data and analysis primitives across AWS, Azure, GCP, and OCI. AI clients use cloudprice-mcp to compute Reserved Instance break-even, multi-cloud workload TCO, exit-cost migration analyses, snapshot cost modeling, and egress arbitrage — the kind of FinOps decisions that normally live in three browser tabs and a half-built spreadsheet.
25 tools covering compute, block storage, object storage, managed Postgres, egress (internet + inter-region with OCI's 10 TB free tier surfaced explicitly), Multi-AZ workloads, snapshots with realistic incremental modeling, Reserved Instance / Savings Plan discounts, FinOps decision suite (migration, commitment, TCO, egress arbitrage), multi-cloud spot pricing with eviction tradeoffs, multi-cloud price history (the only public weekly-refreshed dataset of its kind), a stateless cost drift sentinel for scheduled agents, multi-cloud carbon footprint ($ AND kg CO2e on the same query), multi-cloud GPU pricing (T4 / A10 / L4 / L40S / V100 / A100 / H100 across all 4 clouds), cross-provider LLM token pricing (Claude / GPT / Gemini / Llama / Mistral / DeepSeek across Anthropic / OpenAI / Bedrock / Vertex / Azure OpenAI), statistical price-anomaly detection over the weekly snapshot archive (z-score + percent-change, auto-selected by dataset density), and CFO-grade FinOps decision report generation (markdown reports with executive summary, cost table, carbon, audit trail, honest gaps). OCI Always Free tier (4 OCPU compute, 20 GB object storage, 10 TB egress) surfaced as $0 line items where it applies.
One-line install configures every AI client you have: pip install cloudprice-mcp && cloudprice-mcp setup — auto-detects Claude Desktop, GitHub Copilot Agent Mode, Cursor, Windsurf, Cline, Continue.dev, and Zed, then asks Y/N before writing each config.

Real questions teams actually ask. Paste any of these into Claude / Copilot / Cursor with cloudprice-mcp loaded:
"I have 6× t3.2xlarge running on AWS. Compare the 3-year total cost on-demand vs 1-year Savings Plan vs 3-year RI partial upfront. What's the break-even month?" → AI calls
compare_workload, pulls list-price baseline, layers AWS's published RI rates, returns dollar break-even. ~7-month payback typical.
"I'm thinking about offloading 5 TB of cold-tier object storage from AWS S3 to a cheaper provider. Compare archive-tier cost across all 4 clouds, factor in AWS exit egress, and tell me the payback period." → AI calls
compare_object_storage+compare_egress, computes one-time exit cost vs ongoing savings. Often surfaces "don't move — AWS Glacier Deep Archive is already tied for cheapest".
"At 50 TB/month internet egress, where am I cheapest? Show the 3-year savings of moving." →
compare_egress→ OCI ~$340/mo, AWS/Azure/GCP ~$4,000/mo. The 12× difference is OCI's 10 TB free tier — a real moat for content/CDN workloads.
"Size a 3-tier SaaS workload: 8 web (4/16), 12 app (8/32), 4 DB (16/64), 5 TB shared SSD, 50 TB HDD bulk, 10 TB/month egress. Compare full-stack monthly cost across all 4 clouds with multi-AZ and 1-year commitment." → AI chains
compare_workload+compare_egress, applies multi-AZ multiplier (×2 compute) + commitment discount.
What you get back: dollar numbers traceable to a public catalog, AI-explained tradeoffs, payback periods, and the kind of "don't do that" recommendation that kills bad migrations before they happen. No console-clicking. No tab-switching between three pricing calculators. No FinOps spreadsheet that goes stale the moment a new SKU drops.
Recommended (auto-config):
Then fully restart whichever clients were configured. 10 tools appear in each. Done.
Trust spectrum:
| Command | When to use |
|---|---|
cloudprice-mcp setup | Default — detects every installed client, shows the plan, asks Y/N once |
cloudprice-mcp setup --yes | Skip prompt (CI / scripts) |
cloudprice-mcp setup --client copilot | Configure a specific client (repeatable: --client copilot --client cursor) |
cloudprice-mcp setup --all | Configure every known client even if not detected |
cloudprice-mcp setup --force | Refresh existing entries — useful after upgrade or moving Python |
cloudprice-mcp setup --dry-run | Show per-client diffs without writing |
cloudprice-mcp setup --print-config | Emit per-client JSON to stdout for manual paste |
cloudprice-mcp setup --list-clients | Detection table — which clients are known + installed on this system |
| Manual edit | Don't trust running new tools — see INSTALL.md per-client sections |
If something doesn't work, run:
It tells you exactly what's broken (Python version, install path, config location, tool registration, command path validity).
Python 3.10+ required.
For step-by-step manual install (Windows / macOS / Linux), see INSTALL.md.
| Tool | What it does |
|---|---|
get_aws_price | Look up an EC2 instance type → vCPUs, memory, hourly + monthly USD (us-east-1) |
get_azure_price | Look up an Azure VM size → vCPUs, memory, hourly + monthly USD (eastus) |
get_gcp_price | Look up a GCP Compute Engine machine type → vCPUs, memory, hourly + monthly USD (us-east1) |
compare_clouds | Given a target spec (vCPUs + GB), return the cheapest matching SKU across AWS / Azure / GCP / OCI, sorted by monthly cost, with savings summary |
| Tool | What it does |
|---|---|
compare_compute_inventory | Bulk-compare a list of compute workloads (each with vCPUs / memory / quantity / hours / optional OS disk) across all 4 clouds. Returns per-row matches, per-cloud totals, cheapest cloud. |
compare_storage_inventory | Bulk-compare a list of block-storage volumes (each with capacity / disk type / quantity) across all 4 clouds. |
compare_workload | Combined compute + block storage in one call. Mirrors a two-sheet sizing workbook (compute BoM + storage BoM). Optional commitment overlay applies 1-year (30%) or 3-year (50%) compute discount. |
| Tool | What it does |
|---|---|
compare_object_storage | Bulk-compare object-storage buckets across AWS S3 / Azure Blob / GCP Cloud Storage / OCI Object Storage. Each row specifies capacity_gb + tier (hot / cool / archive). OCI Always Free 20 GB tier surfaced explicitly — capacity ≤ 20 GB on OCI hot tier returns $0/mo. |
compare_postgres_database | Bulk-compare managed PostgreSQL pricing across AWS RDS / Azure Database for PostgreSQL / GCP Cloud SQL / OCI Database with PostgreSQL. Each row specifies vCPUs / memory / storage_gb. Storage cost is calculated separately from compute. |
Four named tools that turn cross-cloud pricing into FinOps decisions in one call instead of letting the AI chain three+ tools. All four consume a structured workload inventory (compute / storage / object_storage / databases / egress) plus tool-specific options.
| Tool | What it does |
|---|---|
assess_migration | "Should I move?" — projects per-target cloud cost, savings %, one-time exit egress cost, payback months. Returns a ranked recommendation by 3-year TCO with triggered caveats (e.g., "OCI A1.Flex is ARM — verify your AMIs"). |
optimize_commitment | "When does my RI / SP / CUD pay back?" — six commitment scenarios (none / 1yr_no_upfront / 1yr_all_upfront / 3yr_no_upfront / 3yr_partial_upfront / 3yr_all_upfront) with per-scenario monthly cost, upfront, 3-year total, savings %, payback months. Recommends the lowest 3-year TCO option. |
compare_total_cost_of_ownership | "What's my 3-year cost across clouds?" — multi-year projection with linear YoY growth assumptions for compute / storage / egress. Returns cumulative TCO per cloud, year-by-year breakdown, sensitivity analysis on the dominant variable. The kind of number that goes into board decks. |
find_egress_arbitrage | "Where do I save on data transfer?" — specialized assess_migration scoped to egress only. Surfaces the OCI 12× moat: at 50 TB/month internet egress, OCI is ~$340 vs $4,000+ on the hyperscalers. |
All four tools accept a WorkloadInventory shape that mirrors a 4-section sizing sheet (compute / storage / object_storage / databases / egress) plus optional commitment, multi_az, and one_time.data_to_migrate_gb fields. Output includes honest_gaps — explicit list of what each tool does NOT model — to prevent over-trust.
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