AI42-MCP X402 Payment Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose with no ambiguity: fetch-with-payment handles data retrieval with payment automation, get-balance checks wallet balance, get-payment-history views session payments, and set-payment-limit configures spending limits. The descriptions clearly differentiate their functions, making misselection unlikely.
Naming Consistency4/5The tool names follow a mostly consistent verb_noun pattern (e.g., fetch-with-payment, get-balance, get-payment-history, set-payment-limit), with all using hyphens for separation. However, fetch-with-payment uses a compound verb (fetch-with) that slightly deviates from the simpler verb forms in the others, but overall the naming is predictable and readable.
Tool Count5/5With 4 tools, the count is well-scoped for a payment server focused on data fetching and wallet management. Each tool earns its place by covering essential operations: data retrieval, balance checking, payment tracking, and limit setting, without being overly complex or sparse.
Completeness4/5The tool surface covers core payment and wallet management workflows effectively, including data fetching with payment handling, balance inquiries, payment history, and limit configuration. A minor gap exists in lacking a tool for direct payment initiation or refunds, but agents can work around this using the existing tools for most scenarios.
Average 3.3/5 across 4 of 4 tools scored. Lowest: 2.6/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'view all payments made during this session', which implies a read-only operation, but doesn't disclose other traits such as authentication needs, rate limits, error handling, or what 'session' entails. This leaves significant gaps in understanding the tool's behavior beyond basic purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that efficiently states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, making it easy to parse, though it could be slightly more structured by including usage context or parameter hints.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (a read operation with one parameter) and no annotations or output schema, the description is incomplete. It lacks details on behavioral traits, usage guidelines, and return values, which are crucial for an agent to invoke it correctly. The description alone is insufficient for full contextual understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the 'limit' parameter fully documented in the schema. The description adds no additional meaning beyond what the schema provides, as it doesn't mention parameters at all. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'View all payments made during this session' clearly states the tool's purpose with a specific verb ('view') and resource ('payments'), but it doesn't differentiate from sibling tools like 'fetch-with-payment' or 'get-balance'. The scope 'during this session' provides some specificity, but the purpose remains somewhat vague regarding what distinguishes it from similar tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'fetch-with-payment' or 'get-balance'. It implies usage for viewing payments in the current session, but lacks explicit when/when-not instructions or named alternatives, leaving the agent to infer context without clear direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While 'Check' implies a read-only operation, it doesn't specify whether this requires authentication, network connectivity, rate limits, or what happens if the wallet doesn't exist. For a financial tool with zero annotation coverage, this leaves significant behavioral questions unanswered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that communicates the essential purpose without any wasted words. It's front-loaded with the core functionality and appropriately sized for a simple read operation with no parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple balance-checking tool with no parameters and no output schema, the description is minimally adequate. However, without annotations covering authentication requirements, network behavior, or error conditions, and with sibling tools that suggest a payment/wallet context, more contextual information would be helpful for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters with 100% schema description coverage, so the schema already fully documents the empty parameter set. The description appropriately doesn't waste space discussing non-existent parameters, maintaining focus on the tool's purpose. Baseline for zero parameters is 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Check') and resource ('current SOL balance in your wallet'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'get-payment-history', but the focus on current balance rather than historical data provides implicit distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get-payment-history' or 'fetch-with-payment'. There's no mention of prerequisites, timing considerations, or comparative use cases with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses key behavioral traits: automatic payment handling for 402 status, which is valuable beyond basic fetching. However, it lacks details on error handling, rate limits, authentication needs, or response format, leaving significant gaps for a tool with mutation potential (payment handling).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with two concise sentences that are front-loaded and zero waste. Each sentence earns its place by stating the core function and a key behavioral trait.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (payment handling mutation with no annotations and no output schema), the description is incomplete. It covers the payment feature but lacks details on prerequisites, side effects, or return values, making it adequate but with clear gaps for safe agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents parameters (url, method, body). The description adds no additional meaning beyond what the schema provides, such as explaining how payment interacts with parameters. Baseline 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('fetch data') and resources ('from a website or API'), distinguishing it from payment-related siblings like get-balance or get-payment-history. However, it doesn't explicitly differentiate from potential generic fetch tools that might exist in other contexts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for fetching data when payment might be required (handling 402 status), providing some context. However, it doesn't explicitly state when to use this vs. alternatives (e.g., standard fetch tools without payment handling) or when not to use it, leaving gaps in guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the action ('Set') and effect ('remove limit'), but lacks details on permissions required, whether changes are reversible, rate limits, or what happens if the limit is exceeded. This is a significant gap for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences that are front-loaded and waste no words. Every sentence earns its place by clearly stating the tool's purpose and usage rule.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (mutation with no annotations and no output schema), the description is adequate but incomplete. It covers the basic purpose and parameter usage, but lacks behavioral context like error handling or response format, leaving gaps for an agent to operate effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents the 'limit' parameter fully. The description adds minimal value by restating the parameter's purpose and the special case of 0, but does not provide additional syntax or format details beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Set maximum amount willing to pay per request') and resource ('payment limit'), with explicit mention of the currency (SOL). It distinguishes from sibling tools like 'get-balance' or 'get-payment-history' by focusing on configuration rather than retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for usage ('Set to 0 to remove limit'), indicating when to use this specific value. However, it does not explicitly mention when to use this tool versus alternatives like 'fetch-with-payment' or any prerequisites, which prevents a perfect score.
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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