cloudprice-mcp

<!-- mcp-name: io.github.alialbaker/cloudprice-mcp -->

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.

16 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), and multi-cloud price history (the only public weekly-refreshed dataset of its kind). 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.

What does FinOps look like with cloudprice-mcp?

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.

---

Install

Recommended (auto-config):

pip install cloudprice-mcp
cloudprice-mcp setup     # auto-configures every detected MCP client, asks Y/N before writing

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:

cloudprice-mcp doctor

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.

Tools exposed

Single-spec lookups (v0.1)

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

Bulk + workload compare (v0.2)

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.

Object storage + managed Postgres (v0.3)

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.

FinOps decision suite (v0.6, NEW)

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.

Egress + Multi-AZ + better snapshots (v0.5, NEW)

Tool / Feature	What it does
compare_egress	Compare data-transfer costs across all 4 clouds. Two directions: out_to_internet (tiered pricing with free-tier credits — AWS/Azure 100 GB, OCI 10 TB) and inter_region (cross-region within the same cloud). At 50 TB/month internet egress, OCI is ~12× cheaper than the hyperscalers — a real moat for content/CDN workloads.
compare_workload multi_az: true	New flag doubles compute totals on every cloud to model Multi-AZ / HA deployments (sync replicas across two zones). Storage stays at 1× because object/block storage is usually cross-AZ at base price.
snapshot_incremental_factor	New per-row field on storage and OS-disk snapshots. Default 1.0 keeps the v0.2 upper-bound estimate. Set to 0.3 for typical real-world incremental dedup, or 0.0 to exclude snapshots from the total.

Example: compare_workload input shape

{
  "compute": [
    { "name": "web", "tier": "Web", "vcpus": 4, "memory_gb": 16, "quantity": 8,  "os_disk_gb": 100, "os_disk_type": "ssd" },
    { "name": "app", "tier": "App", "vcpus": 8, "memory_gb": 32, "quantity": 12, "os_disk_gb": 200, "os_disk_type": "ssd" },
    { "name": "db",  "tier": "DB",  "vcpus": 16, "memory_gb": 64, "quantity": 4, "os_disk_gb": 500, "os_disk_type": "ssd" }
  ],
  "storage": [
    { "name": "shared-fast", "tier": "DB",  "capacity_gb": 5000,  "disk_type": "ssd" },
    { "name": "shared-bulk", "tier": "App", "capacity_gb": 50000, "disk_type": "hdd" }
  ]
}

Snapshots (v0.2.1)

snapshot_count on storage rows and os_disk_snapshot_count on compute rows are now priced. Snapshot rates per cloud per disk type are bundled (~$0.05/GB-mo for AWS/Azure, ~$0.026/GB-mo for GCP).

Caveat — upper-bound estimate: snapshots are priced as snapshot_per_gb_month × full_capacity × quantity × snapshot_count. Real-world snapshots are incremental (only changed blocks), so actual cost is typically 20-50% of this model's number. If snapshots dominate your total, ask the cloud's calculator for a tighter estimate.

iops and throughput_mbs on storage rows are still accepted as metadata only — not used for SKU matching in this release.

Reserved Instance / Savings Plan estimator (v0.2.1)

compare_workload accepts an optional commitment parameter:

Value	Compute discount	Use case
none (default)	0%	On-demand only
1yr_no_upfront	30%	1-year AWS Savings Plan / Azure RI / GCP CUD (no upfront)
3yr_partial_upfront	50%	3-year, partial upfront — typical "we know our baseline" deals

Storage and snapshots are not discounted (most clouds don't offer meaningful storage commitments). Discount tiers are conservative averages — your actual rate depends on instance family, payment option, and region.

Pricing data

Prices are bundled as a curated dataset of common SKUs across 4 clouds:

• Compute (~50 VM SKUs across AWS / Azure / GCP / OCI, including OCI A1 Always Free + A2 Arm Ampere + E5 Flex)
• Block storage (SSD + HDD per cloud)
• Object storage (Hot / Cool / Archive tiers per cloud, including OCI Always Free 20 GB)
• Managed PostgreSQL (RDS / Azure DB / Cloud SQL / OCI Database with PostgreSQL)

Auto-refreshed weekly (v0.7+)

The bundled catalog is refreshed every Sunday by a GitHub Action that hits each cloud's public pricing API:

• AWS — Pricing API (via boto3, OIDC-authenticated)
• Azure — Retail Prices API (public, no auth)
• OCI — Public pricing API (public, no auth)
• GCP — coming in v0.7.1 (requires API key)

Each refresh writes a dated snapshot to src/cloudprice_mcp/data/prices/YYYY-MM-DD.json — every JSON ever published lives in the repo. The history archive is MIT-licensed and grows with every release.

Every tool result includes the catalog's as_of field so you know exactly which prices were used.

Public price history dataset (v0.7.1+)

cloudprice-mcp is the only FinOps tool we know of that preserves every weekly snapshot. You can query "what did m5.xlarge cost in May?" — neither AWS Calculator nor GCP Estimator can answer that because their pages always show today.

Query the history from the CLI:

cloudprice-mcp history --cloud oci --sku VM.Standard.E5.Flex.4OCPU
# oci/VM.Standard.E5.Flex.4OCPU (us-ashburn-1) — 2 data point(s)
#
# AS_OF          HOURLY USD
# --------------------------
# 2026-04-26   $    0.67600
# 2026-05-12   $    0.18400
#
# Change: -72.78% ($-0.49200/h)

The -72.78% drop is the v0.7.0 auto-refresh fixing a hand-curated inaccuracy in the prior OCI catalog — proof that the auto-refresh story works.

Query the history from AI assistants via two new MCP tools:

• get_price_history(cloud, sku, since?) — full timeseries + change stats
• list_tracked_skus(cloud?, since?) — every (cloud, sku) pair we have history for

Real questions this unlocks:

"Has AWS m5.xlarge changed price in the last quarter?" → AI calls get_price_history, returns timeseries with start/end prices and % change.

"Show me every multi-cloud price mover since January." → AI calls list_tracked_skus(since="2026-01-01"), returns every SKU + its latest price + change.

What's NOT modeled (real-world TCO killers)

• ✅ Egress / data transfer — modeled in v0.5 (compare_egress)
• ✅ Multi-AZ / HA replicas — modeled in v0.5 (multi_az: true on compare_workload)
• ✅ Snapshots upper-bound only — fixed in v0.5 (snapshot_incremental_factor)
• Reserved/Savings Plan SKU detail (we apply a flat tier discount, not per-region/per-family detail) — roadmap
• Multi-region pricing (currently us-east only; us-west / eu-west planned for v0.5.1) — roadmap
• IOPS-based storage matching (capacity-only) — roadmap
• Backup storage charges (some clouds free, others billed) — roadmap
• Request costs (PUT/GET pricing for object storage) — roadmap
• Retrieval costs for archive tiers (Glacier-style retrieval can be 10× the storage cost) — roadmap
• VPC peering / interconnect costs — roadmap

These are tracked roadmap items. Use cloudprice-mcp for the on-demand list-price baseline; do final TCO analysis with each cloud's own calculator before relying on numbers for big decisions.

Live runtime pricing (not just weekly refresh) is being considered for v0.8 — would fetch prices directly at MCP tool invocation time instead of from the bundled catalog. Trade-offs: slower (network call per tool use), adds GCP auth requirement, breaks offline mode. The v0.7 weekly auto-refresh covers ~95% of the credibility win at zero runtime cost; live mode is opt-in territory.

Develop locally

git clone https://github.com/Albaker-Group/cloudprice-mcp.git
cd cloudprice-mcp
pip install -e ".[dev]"
pytest

To point Claude Desktop at your dev copy, swap the command in the config:

{
  "mcpServers": {
    "cloudprice": {
      "command": "python",
      "args": ["-m", "cloudprice_mcp.server"]
    }
  }
}

License

MIT — see LICENSE.

Credits

Built by Ali Albaker, multi-cloud architect — runs a live three-cloud portfolio at ~$1.80/month across AWS, Azure, and GCP, with OCI joining as the 4th cloud in 2026.