corpusAI Cloud Pricing

Instance price ladder

term_instance

Read-onlyIdempotent

Paid (0.01 USDC per call). Price ladder for one instance type: spot, on-demand, 1-year and 3-year commitments, with discounts. Current prices from our series: spot median across zones (where spot events exist), on-demand list price, and reserved/reservation terms as effective hourly with upfront amortized. discount_pct is relative to on-demand. AWS carries four reserved terms (1y/3y × no/all upfront), Azure two (1y/3y all upfront), GCP two resource-based committed-use terms (cud_1y, cud_3y, no upfront).

Input Schema

TableJSON Schema

Name	Required	Description
`region`	Yes	Region slug as listed by /catalog (for example `us-east-1` for AWS, `us-central1` for GCP, `us-east` for Azure). Azure slugs map to `eastus`, `westus2`, `westeurope`. Example: us-east-1
`instance`	Yes	Instance / machine / SKU type name exactly as listed by /instances (for example `c5.large`, `n2-standard-4`, `D2s_v5`). Example: c5.large
`provider`	Yes	Cloud provider. One of `aws`, `gcp`, `azure`.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`note`	No
`unit`	No
`terms`	No
`region`	No
`instance`	No
`provider`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 28, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": true,
+  "properties": {
+    "instance": {
+      "type": "string"
+    },
+    "note": {
+      "type": "string"
+    },
+    "provider": {
+      "type": "string"
+    },
+    "region": {
+      "type": "string"
+    },
+    "terms": {
+      "items": {
+        "additionalProperties": true,
+        "properties": {
+          "discount_pct": {
+            "description": "Percent below on-demand.",
+            "type": "number"
+          },
+          "label": {
+            "type": "string"
+          },
+          "price": {
+            "description": "USD per hour for the instance.",
+            "type": "number"
+          },
+          "since": {
+            "type": "string"
+          },
+          "term": {
+            "description": "One of: spot, ondemand, ri_1y_no_upfront_standard, ri_1y_all_upfront_standard, ri_3y_no_upfront_standard, ri_3y_all_upfront_standard, cud_1y, cud_3y",
+            "type": "string"
+          },
+          "zones": {
+            "description": "spot only: zones behind the median.",
+            "type": "number"
+          }
+        },
+        "required": [
+          "term",
+          "price"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "unit": {
+      "type": "string"
+    }
+  },
+  "type": "object"
+}

First observedSep 26, 2026

TDQS

A3.8/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), so the description earns credit for going further: it discloses the per-call cost (0.01 USDC), the data provenance (spot median across zones, only where spot events exist), and the amortization semantics of reserved terms. That is real behavioral context an agent needs before spending on this call.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The paid-call notice is front-loaded, and the rest is dense, information-bearing prose with no filler. The provider-term breakdown is long but each clause carries domain detail; only mild density costs it a point.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, the description need not restate return values, yet it usefully explains the non-obvious `discount_pct` basis and the provider-specific committed-use term universe (AWS 4, Azure 2, GCP 2). For a pricing lookup tool this covers everything an agent needs to interpret results correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so all three parameters (provider, region, instance) are already fully documented with formats and examples. The description adds no param-level detail beyond the schema; the `discount_pct` explanation concerns a returned field, not an input. Baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names the specific resource (price ladder for one instance type) and enumerates exactly what the ladder contains: spot, on-demand, 1y/3y reserved terms. An agent can tell it retrieves pricing for a single instance. It does not explicitly distinguish itself from the closely-named sibling `term`, which is the only real gap.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied rather than stated: the tool returns prices for one instance type, and the 0.01 USDC per-call cost signals it is a metered lookup. There is no explicit when-to-use vs. alternatives guidance (e.g., how it relates to `spot_latest`, `ondemand`, or `reserved`), leaving the agent to infer routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All corpusAI Cloud Pricing tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.