sella

get_dataset

Retrieve full dataset content. Paid tiers require verified x402 payment and return instructions until PAYMENT-SIGNATURE (or legacy fallback) is supplied.

Input Schema

TableJSON Schema

Name	Required	Description
`version`	No	Optional dataset version to buy. Defaults to the latest. A version that does not exist is rejected, never substituted. The response pins the delivered version and its content hash.
`x_payment`	No	Legacy v1 X-PAYMENT header value.
`dataset_id`	Yes	The dataset ID
`payment_proof`	No	Legacy fallback proof used by older clients (historically X-PAYMENT-RESPONSE). Prefer payment_signature. Accepted only when the server explicitly sets X402_ALLOW_LEGACY_RESPONSE_PROOF=true; rejected otherwise.
`payment_signature`	No	Base64 x402 PAYMENT-SIGNATURE header value (v2 preferred).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

Changed1 schema field changedJul 30, 2026

addedInput schema / properties / version

Added value: +{
+  "description": "Optional dataset version to buy. Defaults to the latest. A version that does not exist is rejected, never substituted. The response pins the delivered version and its content hash.",
+  "minimum": 1,
+  "type": "integer"
+}

First observedJul 19, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations indicate readOnlyHint=false and destructiveHint=false, and the description adds context about payment flow and legacy fallback. No contradictions, but doesn't cover failure modes or rate limits.

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

Conciseness5/5

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

Two succinct sentences with no filler. Front-loaded with the core action, followed by critical payment constraint. Every sentence adds value.

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

Completeness4/5

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

Covers main behavior and payment caveat for a tool with 5 params and no output schema. Lacks explicit return description, but version param description compensates. Adequate for the complexity.

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

Parameters4/5

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

Schema coverage is 100%, so parameters are well-documented. The description adds payment context (x402, PAYMENT-SIGNATURE) that explains the purpose of payment-related parameters, adding value beyond schema.

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

Purpose5/5

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

The description clearly states 'Retrieve full dataset content' with a specific verb and resource. It distinguishes from siblings like 'try_dataset' by highlighting payment requirements for paid tiers.

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

Usage Guidelines4/5

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

Description explains when payment is needed (paid tiers) and that instructions are returned until payment is supplied. However, it does not explicitly mention alternatives like 'try_dataset' or when to choose this tool over others.

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

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TDQS

A4/5.0

Disambiguation4/5

Most tools have clearly distinct purposes, but the deprecated tools (list_datasets, list_market_apis, search_datasets, try_dataset) overlap with modern replacements (search_catalog, get_listing). Some functional overlap exists between get_activity and charge_list, but descriptions clarify their scopes. Overall, an agent can usually tell tools apart, with a few legacy remnants.

Naming Consistency5/5

Tool names follow a consistent snake_case verb_noun pattern (browse_catalog, business_start, charge_create, etc.). Even the deprecated tools adhere to the same style. There are no mixed conventions or vague verbs like 'process' or 'run'. The naming is highly predictable.

Tool Count3/5

At 52 tools, this is a large surface. The domain is broad (marketplace buying/selling, business management, policy, storefront, distribution, authentication), so many tools are justifiable. However, four deprecated tools could be pruned, and the count is on the heavy side compared to typical MCP servers. It feels overengineered, yet each tool addresses a distinct facet of the platform.

Completeness4/5

The toolset covers the full lifecycle: discovery, evaluation, purchase, delivery, feedback, business management, policy, storefront, and distribution. Gaps are minor—for example, no direct way to list all services with full details without service_list, but that exists. The deprecated tools indicate ongoing migration to a consolidated search surface, suggesting good coverage. A few small gaps remain (e.g., no explicit 'update listing' for buyers, but that may not be needed).

Resources

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