site
Server Details
ADR Courses: the site's own MCP server — enquiry (enquiry = a human handoff, not a purchase);...
- 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 ADR Courses: 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 full burden of behavioral disclosure. It clearly states what the tool returns—who receives details, consent wording, and confirmation method—and clarifies that nothing is bought, ordered, or paid and no quote is guaranteed. This gives the agent a solid understanding of the tool's informational nature.
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 front-loaded with 'Read first' and 'States plainly,' and each sentence carries meaningful information. It is slightly wordy but not padded, and the structure logically moves from purpose to constraints to return 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 zero-parameter, no-output-schema tool, the description is remarkably complete. It explains the tool's purpose, what it clarifies about the enquiry process, key caveats, and exactly what it returns, leaving little ambiguity for an agent deciding to call it.
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 parameters, so the baseline is 4. The description adds contextual meaning about what the tool communicates, which is useful even though no parameter documentation 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 the tool's purpose: it 'States plainly what submit_enquiry does on ADR Courses.' This is a specific verb-resource pairing and distinguishes it from the sibling submit_enquiry tool by making clear it describes rather than performs the enquiry.
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 'Read first' is an explicit usage cue, signaling that this tool should be consulted before using submit_enquiry. It establishes context for when to use the tool, though it does not explicitly name alternatives or exclusions beyond the implied contrast with submit_enquiry.
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 ADR Courses 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 must carry the burden. It conveys that this is an inspection/metadata tool with no inputs and enumerates expected output attributes, which implies a read-only lookup. It does not explicitly state a return format, authorization requirements, or error behavior, but the simple, zero-parameter nature limits the severity.
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 efficient sentences front-load the tool's purpose and then supply the key integration detail. Every phrase contributes; there is no redundant filler.
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 metadata tool with no output schema, the description is complete: it names the return fields, scales to the full enquiry, and ties to submit_enquiry. No missing behavior is necessary for correct invocation.
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 and the schema covers that completely, so parameter-semantic work is already done. The description adds no parameter explanations, which is appropriate; it instead clarifies output keys for downstream submission.
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 identifies the resource (fields of the ADR Courses enquiry) and the content return (key, label, type, required, help text, allowed options). It differentiates from submit_enquiry by telling agents to key answers with these fields, though it does not explicitly distinguish itself 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?
The final sentence gives concrete guidance: answers passed to submit_enquiry must be keyed by these field keys. This implies the tool's role in the submission flow, but it never states when to choose this tool over enquiry_describe or mentions exclusions.
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 ADR Courses — 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 approved ADR training centres, who'll quote 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 approved ADR training centres, who'll quote 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 fully carries the behavioral burden. It discloses the validation step, required consent text, confirmation token flow, email delivery, and the link-click requirement before providers see the enquiry. This is far more transparent than typical tool descriptions.
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 almost every clause carries operational necessity. It is front-loaded with the core purpose and the 'not a purchase' warning. Minor structural improvements could be made, but it is not bloated or redundant.
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 tool involves a complex two-step workflow with consent and email confirmation, and the description covers all critical aspects: what to show the person, when to call again, what token to pass, and what happens after submission. There is no output schema, so the description's explanation of return values is especially valuable.
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%, so the baseline is 3. The description adds meaningful context beyond the schema by explaining that answers are keyed by field keys from enquiry_fields, that consent must be exactly true with the quoted consent line, and how confirmation ties into the two-step flow. It stops short of listing possible field keys, but that is delegated appropriately.
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 and resource: 'Submits an enquiry to ADR Courses'. It also explicitly distinguishes this from a purchase and from a guaranteed quote, making the tool's role unambiguous even without comparing to sibling names.
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 an explicit two-step calling protocol: step 1 for validation and token retrieval, step 2 only after the person agrees. It also includes when-not guidance ('NOT a purchase') and references enquiry_fields for obtaining valid answer keys, which helps the agent choose the right path.
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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"claim": "glama_claim_..."
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TDQS
enquiry_describe, enquiry_fields, and submit_enquiry address clearly distinct concerns: process explanation, field schema, and validated submission. There is no meaningful overlap that would cause an agent to select the wrong tool.
enquiry_describe and enquiry_fields share an object-first 'enquiry_*' pattern, but submit_enquiry inverts this to verb-first. The mixed convention is still readable, but not fully predictable.
Three tools map neatly to the enquiry workflow: understand the process, get the field schema, and submit with confirmation. Each tool earns its place and the scope is tightly focused.
The workflow is complete for the domain: an agent can discover the process, obtain the form schema, validate a submission, and confirm with a token. No additional lifecycle operations are needed for this single-submission flow.