Solana MCP by Vybe

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

Annotations already declare destructiveHint=true and readOnlyHint=false, so the mutating nature is known. The description adds no additional behavioral context (e.g., side effects, rate limits, server interactions) beyond what the annotations imply. It does not contradict the annotations, but offers no extra disclosure, hence a neutral score.

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?

The description is a single, efficient sentence with no redundant words. It clearly identify the action and the input format. While it is minimal, it is not verbose, and the structure is appropriate, though it could have incorporated usage guidance without sacrificing clarity.

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?

For a tool that is destructive and open-world (as flagged by annotations) and has no output schema, the description is too sparse. It does not explain what the tool returns, potential side effects, error conditions, or how it differs from simply defining a request. An agent would lack critical information to safely and effectively invoke this tool in a real workflow.

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 schema describes the harRequest parameter in detail, including sub-fields like url, method, headers, postData (with distinctions between text and params), and queryString. Schema coverage is 100%, meeting the baseline. The description only says 'given HAR request object,' adding no semantic value beyond what the schema already provides.

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 a specific action ('Executes an API request') and identifies the input format ('given HAR request object'). This distinguishes it from sibling tools that are about searching/listing endpoints rather than executing requests. However, it is somewhat generic and could be more explicit about what 'execute' entails.

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention sibling tools or any conditions that would select this tool over others. The presence of read-only siblings like search-endpoints and get-endpoint makes this gap significant; an agent has no explicit direction on when to perform an actual request.

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

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

Annotations already declare readOnlyHint=true, so the description need not belabor safety. It adds useful context that the response includes security schemes and servers, which informs response expectations. However, it does not disclose other behavioral traits such as error handling, rate limits, or the full response structure. With annotation coverage, this is adequate but not rich.

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?

A single, well-structured sentence that front-loads the action and resource. No wasted words, and the mention of security schemes and servers gives a concrete sense of scope. Efficient and immediately scannable.

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?

For a simple read-only endpoint tool with two well-documented parameters and a readOnly annotation, the description is reasonably complete. It specifies the tool's purpose and hints at response content. However, without an output schema, an agent might want more detail on the full response fields, though 'detailed information' plus the named examples may suffice for this low-complexity tool.

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?

Schema description coverage is 100%, so both parameters (path and method) are fully documented in the input schema. The description adds no extra semantic meaning beyond what the schema already provides. Baseline of 3 applies because the schema carries the heavy lifting.

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 a specific verb ('Gets'), a resource ('detailed information about a specific API endpoint'), and highlights notable content (security schemes and servers). It implies a targeted operation distinct from list/search siblings, though it does not explicitly name alternatives. Clear enough for an agent to understand what the tool does.

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?

No guidance is provided on when to use this tool versus siblings like list-endpoints or search-endpoints. There is no mention of typical use cases, preconditions, or when to prefer an alternative. The agent must infer from the name and description alone, which offers no explicit direction.

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

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

Annotations already carry the safety profile (readOnlyHint=true), and the description's 'Lists' wording is consistent with a non-mutating read. The description adds minor context beyond annotations — the 'organized by path' structure and the pass-through to get-endpoint — but does not detail output shape or any edge cases, which annotations alone don't fully cover.

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 compact sentences with no filler. The core purpose is front-loaded, and the second sentence earns its place by enabling a chaining workflow. Minor ambiguity in 'organized by path' is the only slight inefficiency, but overall it is tight.

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?

For a parameterless list tool with no nested objects, the definition is nearly complete. The only gap is that there is no output schema and the description doesn't enumerate the properties each endpoint entry carries; the reference to get-endpoint implies a compatible structure but leaves the exact format unstated.

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?

With zero parameters, the baseline of 4 applies per the rubric. There is nothing for the description to document, and the phrasing implicitly signals the tool takes no arguments (it returns the whole set). It neither adds nor needs parameter-level detail.

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 names a specific verb ('Lists'), a resource ('all API paths'), and what each entry includes (HTTP methods and summaries) with an organizational detail (by path). This clearly distinguishes it from siblings like get-endpoint (single endpoint) and search-endpoints (filtering), since listing all is the differentiator.

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?

The description provides useful workflow context by noting results 'can be passed directly into get-endpoint,' which tells an agent how to chain calls. However, it gives no explicit when-to-use vs when-not-to guidance and never mentions search-endpoints as an alternative for filtered discovery, leaving the selection decision partly to inference.

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

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

Annotations provide readOnlyHint=true, which already declares safety. The description adds that it uses 'x402 pay-per-call USDC on Solana' but does not explain the actual behavior: Does it return a payment link? Does it redirect to a wallet? Does it require user interaction? Does it charge immediately? Without this, an agent cannot predict what happens after calling this tool. The description does not contradict the read-only hint, but it fails to disclose the operational flow, which is a significant gap for a no-parameter tool with no output schema.

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?

The description is a single, front-loaded sentence that immediately states the primary use case and the alternative condition. Every word earns its place—no fluff, no repetition. It efficiently communicates when and why to use the tool.

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?

Given the tool has no inputs and an output schema is absent, the description should at least hint at what the agent receives or what happens next. It explains the 'when' but not the 'what does it do' beyond 'access the endpoint.' This leaves the agent uncertain about how to integrate its result. The complexity is low, but the description is incomplete for an agent that needs to chain this with a downstream request.

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 the schema is trivially complete. Per the rubric, a tool with no parameters gets a baseline of 4. The description adds no parameter information because there is none to add, which is appropriate. No deduction is needed.

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 that the tool is for accessing Vybe endpoints without an API key via x402 pay-per-call USDC on Solana. It names a specific action ('use this to access the same endpoint') and a resource ('Vybe endpoint'), which is distinct from the sibling execute/get/list/search tools that focus on direct endpoint operations. However, it doesn't explicitly say what the tool returns or how it differs from actually calling the endpoint, so it's not a perfect 5.

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?

The description explicitly tells the agent when to use this tool: 'Before calling any Vybe endpoint without an API key' and gives examples of scenarios (AI agent, throwaway script, premium-only path). It also implies the alternative—when an API key is available, you don't use this tool. This is a clear usage directive with no ambiguity, and it references the sibling tools by implication (the endpoint-calling tools).

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

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

Annotations declare readOnlyHint=true and openWorldHint=false, so the safe read behavior is already captured. The description adds the notion of 'deep search' and that results are 'relevant API endpoints,' but doesn't disclose specifics like whether it searches full content or just metadata, pagination, or result limits. It also doesn't state that it's case-insensitive (that's in the schema), but that's fine. Overall, some added context but not rich behavioral detail beyond annotations.

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?

The description is two sentences with no filler. It states what the tool does, when to use it, and how to use the results—all in a front-loaded manner. Every sentence earns its place and it is appropriately sized for a single-parameter search tool.

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?

For a search tool with only one parameter and no output schema, the description covers the purpose, usage, and output chaining. It lacks some behavioral details like whether results are paginated or how many results are returned, but given the simplicity, these seems minor. The tool appears complete enough for an agent to invoke correctly.

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?

Schema coverage is 100% because the only parameter 'pattern' is described in the schema as 'Search pattern (case-insensitive)'. The description doesn't add additional meaning about the parameter format beyond implying it's a keyword search. Since coverage is high and the description reinforces the purpose, a score above baseline is justified, but not the maximum because there's no extra detail about how patterns are matched (e.g., regex, wildcards).

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 it 'Performs a deep search through paths, operations, and parameters to discover relevant API endpoints.' It identifies the specific verb (search) and resource (API endpoints) and differentiates itself from siblings like 'get-endpoint' and 'list-endpoints' by focusing on discovery via search rather than retrieval or listing. However, it doesn't mention the 'pattern' parameter by name, though the purpose is understandable.

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?

The description tells when to use it: 'Use this tool to find specific API capabilities, required parameters, or data models based on search keywords.' It also indicates how to chain the results: 'Results can be passed directly into 'get-endpoint'.' This gives clear context for when to invoke this tool versus alternatives, though it doesn't explicitly state when NOT to use it (e.g., when you already have an endpoint ID).

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