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Inferventis — Financial Data, News & Web MCP

stripe_payment_records

Retrieves payment and charge records from a Stripe merchant account. Returns a list of payment records filtered by the requested query type. Use stripe_payment_records when an agent needs to review recent charges, refunds, disputes, or subscription payments from a Stripe account. This is a lightweight variant of stripe_payments — it returns a simple records array rather than the full structured Stripe response with customer details, metadata, and pagination cursors. Prefer stripe_payments when the agent needs complete Stripe charge objects including customer IDs, payment method details, metadata fields, and processing status breakdowns. Prefer open_banking_transactions or bank_accounts when the payment data source is a bank account rather than a Stripe merchant account. Requires a Stripe API key to be configured on the server.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of records to return. Defaults to 10. Maximum 50.
query_typeYesType of payment records to retrieve. Accepted values: 'recent_payments' (latest charges), 'refunds' (refund records), 'disputes' (disputed charges), 'subscriptions' (recurring subscription payments).

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the return format ('simple records array'), the filtering mechanism, the limitation compared to stripe_payments (no customer details, metadata, pagination cursors), and the authentication requirement ('Requires a Stripe API key to be configured on the server'). The only minor gap is not detailing exact record fields or error behavior, but the description strongly conveys the tool's behavior.

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?

The description is efficiently structured with five sentences, each serving a distinct purpose: core function, usage context, differentiation from stripe_payments, alternative recommendations, and authentication requirement. It is front-loaded with the main purpose and contains no redundant or unnecessary information.

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?

The description is comprehensive for a simple read tool, covering the action, filtering, limitations, alternatives, and a prerequisite. Since no output schema exists, it could explicitly list the fields in the returned records, but the characterization as a 'simple records array' and the lightweight scope make this acceptable. Overall, it is quite complete for the tool's complexity.

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?

The input schema already covers 100% of parameters with descriptions for limit (default/max) and query_type (accepted values). The tool description paraphrases the query types (recent charges, refunds, etc.) without adding new semantic details, so the baseline score of 3 is appropriate.

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 explicitly states 'Retrieves payment and charge records from a Stripe merchant account' and 'Returns a list of payment records filtered by the requested query type,' clearly identifying the action and resource. It further distinguishes itself from stripe_payments by calling itself a 'lightweight variant,' making the purpose unambiguous and differentiating it from sibling tools.

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

Usage Guidelines5/5

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

The description provides explicit when-to-use guidance: 'Use stripe_payment_records when an agent needs to review recent charges, refunds, disputes, or subscription payments from a Stripe account.' It also names alternatives: 'Prefer stripe_payments when the agent needs complete Stripe charge objects' and 'Prefer open_banking_transactions or bank_accounts when the payment data source is a bank account.' This fully covers usage context and exclusions.

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

A3.9/5.0
Disambiguation3/5

Many tools have overlapping purposes, especially in currency conversion (5 tools) and financial calculations (2 tools). While descriptions are detailed and try to differentiate, the sheer number of similar tools could confuse an agent. The platform_tool_finder tool helps but doesn't fully resolve ambiguity.

Naming Consistency3/5

Naming follows snake_case but is inconsistent: some tools use noun_verb (e.g., currency_convert), others noun_noun (e.g., bank_accounts). There are also variants with suffixes like '_lite' and '_open' which help, but the pattern varies across the set.

Tool Count4/5

20 tools is reasonable for a financial data and news server, covering stocks, crypto, fiat, banking, payments, calculations, and web content. However, there is redundancy (5 fiat converters) that could be streamlined, making the count slightly higher than ideal.

Completeness4/5

The tool set covers a broad range of financial tasks: real-time stocks, crypto, fiat conversion, bank transactions, payments, financial calculations, news, and web reading. Minor gaps exist, such as lack of historical stock data or portfolio tracking, but most common queries can be handled.