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Server Details
Patent Attorney Cost: the site's own MCP server — enquiry (enquiry = a human handoff, not a...
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Available Tools
3 toolsenquiry_describeWhat you get: an ENQUIRY with a human (not a purchase, not a guaranteed quote)AInspect
Read first. States plainly what submit_enquiry does on Patent Attorney Cost: it starts an enquiry with human providers who quote directly. Nothing is bought, ordered or paid; no quote is guaranteed; it is free. Also returns who receives the details, the consent wording, and how the person confirms.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure, and it does so well by stating that nothing is bought, ordered, paid, or guaranteed, and that the enquiry is free. It also discloses what the tool returns: recipients, consent wording, and confirmation method. The only minor gap is that it does not explicitly say the describe tool itself has no side effects, though the wording strongly implies 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 description is only three sentences and front-loads the most important usage instruction ('Read first'). Every sentence contributes either the tool's purpose, the key disclaimers, or the return contents, with no filler or unnecessary technical detail.
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 informational tool with no output schema, the description covers the essential ground: what the tool does, what it clarifies, and what it returns. It is nearly complete, but it does not position itself relative to enquiry_fields, leaving the sibling relationship to be inferred from context signals rather than the description.
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 input schema is empty and has 100% description coverage, so there are no parameters to document; the baseline of 4 applies. The description still adds context about the output contents, which helps set expectations even though no parameters are involved.
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 uses a specific verb ('states') and identifies the exact resource ('what submit_enquiry does on Patent Attorney Cost'), making it clear this is an informational tool rather than the submission action itself. It explains the core facts of the enquiry process, but it does not explicitly distinguish itself from the sibling tool enquiry_fields, so it stops short of full sibling differentiation.
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 opening directive 'Read first' clearly tells the agent to use this tool before submit_enquiry, establishing the intended sequencing. However, it does not explicitly state when not to use this tool or directly contrast it with enquiry_fields, leaving some usage context implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
enquiry_fieldsThe questions the enquiry asksAInspect
Every field of the Patent Attorney Cost enquiry: key, label, type, whether required, help text and the allowed options where there are any. Pass answers to submit_enquiry keyed by field key.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries behavioral disclosure. It explicitly enumerates the output contents (key, label, type, required, help text, options), and the absence of parameters implies a read-only lookup. It does not mention potential side effects, but none are suggested.
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 tightly written sentences: the first front-loads the exact content returned, the second connects to submit_enquiry. No wasted words or redundant schema repetition.
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 parameters, no output schema, and no annotations, the description fully covers what the agent can expect and how to use the result. Nothing necessary for correct invocation is missing.
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 input schema has zero properties, so there are no parameters to describe. The description focuses on the output and the next action, which is appropriate for a parameterless tool.
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-and-resource: it lists every field of the Patent Attorney Cost enquiry, enumerating the field attributes returned. This clearly differentiates it from submit_enquiry, which would accept answers, and from enquiry_describe.
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 precisely when to use the tool (when you need to enumerate the enquiry's fields) and instructs the agent to pass answers to submit_enquiry keyed by field key. It does not explicitly exclude alternatives such as enquiry_describe, but the role is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
submit_enquirySubmit an ENQUIRY to human providers (two steps; not a purchase)AInspect
Submits an enquiry to Patent Attorney Cost — NOT a purchase, NOT a guaranteed quote. Step 1: call with the answers (keyed by field key from enquiry_fields) and consent=true; it validates and returns a summary, the consent line and a confirmation token — show the person the summary and the consent line. Step 2: only if the person agrees, call again with the same answers, consent=true and the confirmation token; the enquiry is then submitted, and the person receives an email with a link they must click before any provider sees it. Consent means the person has read and agreed to: "Happy for my details to go to relevant patent attorneys, who'll contact me directly."
| Name | Required | Description | Default |
|---|---|---|---|
| answers | Yes | the person's answers, keyed by field key | |
| consent | Yes | true only when the person has agreed to: Happy for my details to go to relevant patent attorneys, who'll contact me directly. | |
| confirmation | No | the confirmation token from step 1, after the person has approved the summary |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral disclosure burden. It reveals that the tool is two-step, non-purchase, sends an email with a clickable link, and prevents providers from seeing the enquiry until the person clicks. It even states the exact consent wording.
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 long but every sentence earns its place by covering essential behavioral and procedural information. The Step 1/Step 2 structure makes it easy to follow, and the consent text is included verbatim to prevent misinterpretation.
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?
The description thoroughly explains the two-step flow, the return of summary and token in step 1, the email-link behavior, and the consent requirement. A minor gap is that the return value or success behavior of the second call is not explicitly described, but overall this is highly complete for an agent to use 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?
The schema already covers all three parameters, and the description adds meaningful context: answers must be keyed by field keys from enquiry_fields, confirmation is the token from step 1, and consent requires explicit agreement to the quoted text. This goes beyond the baseline schema coverage.
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 uses a specific verb and resource: 'Submits an enquiry to Patent Attorney Cost.' It also explicitly distinguishes this from a purchase or a guaranteed quote, which removes ambiguity about the tool's true purpose and separates it from sibling tools like enquiry_describe and enquiry_fields.
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 a clear, step-by-step usage protocol: call once with answers and consent, show the summary, then call again with the confirmation token only if the person agrees. It also states when not to use the tool (not for purchases) and the condition that must be met before submission.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
3 tool updates
- First observed
enquiry_describe - First observed
enquiry_fields - First observed
submit_enquiry
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TDQS
Each tool has a clearly distinct purpose: one explains the process, one returns the field schema, and one performs the submission. There is no real overlap in what an agent would call them for.
The names are readable and consistently snake_case, but they do not follow a single pattern: enquiry_describe and enquiry_fields are noun-first, while submit_enquiry is verb-first. This is mixed but not chaotic.
Three tools is well-scoped for a narrow single-purpose enquiry flow. Each tool has a distinct role and none feel redundant or missing.
The set covers the full lifecycle of the enquiry: understanding the flow, retrieving valid input fields, and submitting with confirmation. The two-step confirmation handling is built into submit_enquiry, so there are no dead ends.