dump_llm_pricingDataset download: $1 USDC via x402. Full dump: list prices of ~3,000 AI models (LiteLLM table, MIT) + verified AI/dev free tiers with limits (JSON).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| models | No | ||
| license | No | ||
| sources | No | ||
| free_tiers | No | ||
| generated_at | No |
Changes observed during successful MCP inspections.
Output schema / descriptionPrevious value: -"Inferred from a real response captured on 2026-10-24; extra fields may appear, null-valued fields are untyped."New value: +"Inferred from a real response captured on 2026-10-26; extra fields may appear, null-valued fields are untyped."Output schema / (root)Previous value: -nullNew value: +{
+ "description": "Inferred from a real response captured on 2026-10-24; extra fields may appear, null-valued fields are untyped.",
+ "properties": {
+ "free_tiers": {
+ "items": {
+ "properties": {
+ "alive": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "auth": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "category": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "checked_at": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "cors": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "description": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "free_tier_details": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "http_status": {
+ "type": [
+ "number",
+ "null"
+ ]
+ },
+ "https": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "kind": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "name": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "url": {
+ "type": [
+ "string",
+ "null"
+ ]
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "generated_at": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "license": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "models": {
+ "items": {
+ "properties": {
+ "cached_input_per_m_usd": {
+ "type": [
+ "null",
+ "number"
+ ]
+ },
+ "context_length": {
+ "type": [
+ "number",
+ "null"
+ ]
+ },
+ "free": {
+ "type": [
+ "boolean",
+ "null"
+ ]
+ },
+ "function_calling": {
+ "type": [
+ "boolean",
+ "null"
+ ]
+ },
+ "id": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "input_per_m_usd": {
+ "type": [
+ "number",
+ "null"
+ ]
+ },
+ "max_input_tokens": {
+ "type": [
+ "number",
+ "null"
+ ]
+ },
+ "max_output_tokens": {
+ "type": [
+ "number",
+ "null"
+ ]
+ },
+ "output_per_m_usd": {
+ "type": [
+ "number",
+ "null"
+ ]
+ },
+ "provider": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "reasoning": {
+ "type": [
+ "boolean",
+ "null"
+ ]
+ },
+ "rpm": {},
+ "tpm": {},
+ "vision": {
+ "type": [
+ "boolean",
+ "null"
+ ]
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "sources": {
+ "items": {
+ "properties": {
+ "license": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "name": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "note": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "snapshot": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "url": {
+ "type": [
+ "string",
+ "null"
+ ]
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint, so the description is not burdened with safety disclosure. It adds important behavioral context by stating the cost ($1 USDC via x402), the dataset size, and the JSON format, which an agent needs to know before invoking a paid download.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two tight sentences with no wasted text. The payment requirement and dataset contents are front-loaded, so the agent gets the key facts immediately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With zero parameters, an output schema, and annotations covering safety/openness, the description supplies the remaining essentials: cost, contents, licensing, and format. It is nearly complete, though it could explicitly position itself against the related pricing and sample tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so there is no parameter semantics to explain. A baseline of 4 is appropriate because the description does not need to compensate for an input schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the resource and scope: a full dump of prices for ~3,000 AI models plus verified free tiers, delivered as JSON. The verb 'Dataset download' and the content are specific, but it does not explicitly differentiate this full dump from sibling tools like llm_pricing or llm_pricing_sample.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit guidance on when to use this tool versus alternatives such as llm_pricing, llm_pricing_sample, or free_tiers. The phrase 'Full dump' implies bulk use, but the agent must infer that from context rather than from stated conditions or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.