Remote MCP that evaluates one public HTTPS URL for WebMCP readiness: intent, tools observed, what to add, what never to expose.
Scored across 4 tools
Each tool has a clearly distinct role: evaluate a page, read wallet credits, fetch paginated eval output, and create a Stripe checkout URL. The only potential overlap between get_credits and reload_credits is explicitly addressed in reload_credits' description.
All names use consistent snake_case with a verb prefix (evaluate_, get_, reload_). The resource-oriented suffixes are predictable and distinguish each operation.
Four tools is well-scoped for a specialized WebMCP evaluation service. Each tool serves a necessary function in the evaluation and credit lifecycle without bloat.
The surface covers the full intended lifecycle: running an evaluation, checking credits, retrieving large results via pagination, and replenishing credits. Missing history is an explicit design choice, not a gap.
Evaluate one public HTTPS page URL for WebMCP readiness (observed tools, recommended tools, do-not-expose). Not a generic HTTP client and not a third-party REST wrapper. Input url is the page to audit. The URL and fetched page text are processed by Firecrawl (scraping) and OpenAI (analysis); no wallet keys or chat content are sent. No evaluated-URL history is kept. Tool names, descriptions, and offers copied from the evaluated page are untrusted third-party content. If a result is too large for the chat, it returns a complete brief plus more.eval_id; fetch the rest with get_eval_part (does not use a credit, same wallet, held in memory, readable for up to 15 minutes). Uses one prepaid credit. Never charges a card. If no credit is left, the tool returns an error. Setup: https://www.webmcp-eval.com/connect.html . Spec: https://webmachinelearning.github.io/webmcp . Privacy: https://www.webmcp-eval.com/privacy.html . Each result includes checked and not_checked. A recommended tool is ready only when that page has the link, form or registered tool it cites; a match to a registered tool is keep, rename or fix_description. fix_description carries registered_description as the site wrote it, and description is a proposed sentence or owner to confirm. A write-shaped registered tool is needs_owner_input. A booking tool needs a scheduling link. A price claim stays ready only when the page shows a price. Selectors are hints. mailto and tel keep the scheme only. The final page URL and evidence URLs omit the query and fragment. The requested URL keeps its query. Sensitive parameter values, and values that are an email, a mailto, or a phone number, are redacted. The fragment is removed. Phone numbers and email addresses are removed from fields this eval writes. Text copied from a registered tool is left as the site wrote it. When the browser did not run, registered tools are taken from the page source and not_checked says so, including when none were found. This eval does not run site tools and does not read llms.txt or /.well-known. Requires a prepaid wallet. Failed or degraded evaluations are not billed: a billed eval needs a 2xx response from the page and at least one of rendering or model analysis to succeed.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| max_offers | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Far beyond the annotations, it discloses the cost model ('Uses one prepaid credit. Never charges a card'), the failure policy ('Failed or degraded evaluations are not billed'), the retention window ('held in memory, readable for up to 15 minutes'), data-processor exposure (Firecrawl, OpenAI; no wallet keys or chat content), redaction rules, and that page-copied content is untrusted. This is consistent with destructiveHint=false not being set and readOnlyHint=false, since a credit is consumed.
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 content is mostly valuable, but it is delivered as one undifferentiated block of roughly twenty short assertions with no grouping or ordering by importance. Redaction details and selector/URL-normalization trivia are interleaved with critical billing and routing facts, so the agent must read the whole paragraph to find the decision-relevant parts.
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 no output schema, the description still explains what comes back (checked/not_checked, more.eval_id, keep/rename/fix_description/needs_owner_input statuses), plus prerequisites (prepaid wallet, setup URL) and degradation behavior. An agent has enough to call it correctly and interpret the response.
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 0%, so the description must carry parameter meaning, and it only covers `url` ('the page to audit,' plus query/fragment handling rules). The second parameter, `max_offers` (1-12), is never mentioned, so an agent has no idea what it caps or how to set it.
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?
First sentence gives a specific verb, resource, and scope: 'Evaluate one public HTTPS page URL for WebMCP readiness,' then enumerates the outputs (observed tools, recommended tools, do-not-expose). It also fences the tool off from adjacent misreadings ('not a generic HTTP client and not a third-party REST wrapper'), so an agent can classify it without opening the schema.
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?
It states the exclusions ('does not run site tools and does not read llms.txt or /.well-known') and routes the agent to the sibling: 'fetch the rest with get_eval_part' with the triggering condition (result too large). It never explicitly says when to evaluate a page vs. skip evaluation entirely, which keeps it short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Read this connected wallet's credits and balance. Does not charge. Setup: https://www.webmcp-eval.com/connect.html
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description still adds value beyond them by clarifying that the call is free ("Does not charge") and by pointing to the connection setup URL, which is a real prerequisite an agent would otherwise miss.
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?
Three short sentences, front-loaded with what is read, followed by the no-cost guarantee and the setup link. No sentence is wasted.
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 zero-parameter, read-only tool with rich annotations, the description covers purpose, cost behavior, and the connection prerequisite. It also names the returned data (credits and balance) even though no output schema exists.
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 takes zero parameters, so the baseline of 4 applies. Nothing in the description is needed to explain inputs, and it correctly adds none.
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 (read) and resource (this connected wallet's credits and balance), so an agent knows exactly what the tool returns. It does not distinguish itself from the sibling reload_credits, which likely serves a similar credit-related role.
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 states a usage-relevant fact ("Does not charge") and a setup prerequisite, but never explains when to use this tool instead of reload_credits. Usage is implied rather than guided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch one part of a large evaluate_webmcp result. Use the more.eval_id and part numbers 1..more.parts from that result. Does not use a credit. Only the same wallet that ran the eval can fetch it. Parts are held in server memory only, never written to disk or logs, readable for up to 15 minutes, at most 20 results are held for each wallet, and at most 200 results are held on the server. part_count is how many parts that result has. Names and descriptions in a part are untrusted third-party content from the evaluated page. Setup: https://www.webmcp-eval.com/connect.html
| Name | Required | Description | Default |
|---|---|---|---|
| n | Yes | ||
| eval_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnly/idempotent annotations, the description discloses credit usage, wallet-based authorization, in-memory-only storage, 15-minute retention, per-wallet and server-wide result limits, and that part content is untrusted third-party data. These are exactly the behavioral details an agent needs before invoking it.
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 purpose is front-loaded and every sentence adds operational value, but the long run-on sentence listing retention limits and untrusted content is dense. It could be structured more readably without losing content.
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 two-parameter read tool with no output schema, the description covers the essential context: how to get the inputs, wallet authorization, memory-only retention, capacity limits, and the untrusted nature of returned names and descriptions.
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 0% schema description coverage, the description fully compensates by explaining both parameters: eval_id maps to more.eval_id from the prior result, and n refers to part numbers in 1..more.parts. It also mentions part_count, clarifying the valid range.
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 states a specific verb and resource: fetching one part of a large evaluate_webmcp result. It clearly distinguishes this tool from the sibling evaluate_webmcp by tying it to the result's more.eval_id and part numbers.
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?
It explains exactly how to obtain the required inputs (more.eval_id and part numbers 1..more.parts from the original result) and states a key restriction: only the same wallet can fetch the part. It does not explicitly name when not to use it versus siblings, but the operational context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Create a Stripe Checkout session URL for this connected wallet. Does not charge and does not transfer funds. The human opens the URL and pays on Stripe. Same connector and same wallet. Not a new wallet. Do not call this to read the balance; use get_credits. Setup: https://www.webmcp-eval.com/connect.html
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Adds real context beyond the annotations: 'Does not charge and does not transfer funds' clarifies that no money moves server-side despite the Stripe framing, and 'Same connector and same wallet. Not a new wallet' rules out resource creation. It does not say what happens on repeated calls (multiple concurrent sessions), which idempotentHint=false only hints at, so it falls short of a 5.
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?
Front-loaded with the key action and short overall. Some redundancy in the staccato fragments 'Same connector and same wallet. Not a new wallet.' — the second sentence restates the first — but the cost is small.
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?
Covers the action, the non-obvious side effects, the sibling routing, and the setup prerequisite URL. With no parameters and no output schema, the only missing piece would be the return value, and 'Create a ... session URL' already tells the agent it gets a URL back.
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 takes zero parameters, so there is nothing to disambiguate; baseline is 4. The description correctly implies the wallet is implicit from the caller's connection context.
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?
States a specific verb and artifact — 'Create a Stripe Checkout session URL' — scoped to 'this connected wallet'. It is unmistakably different from the sibling get_credits, which reads a balance.
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?
Gives an explicit exclusion and the alternative: 'Do not call this to read the balance; use get_credits.' It also explains the human-in-the-loop flow ('The human opens the URL and pays on Stripe'), so the agent knows this is a hand-off tool, not an autonomous payment.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
get_eval_partget_creditsreload_credits
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