site
Server Details
CCTV Installation 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 CCTV Installation 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 full burden and meets it well. It explicitly states that nothing is bought, ordered, or paid, that no quote is guaranteed, that the enquiry is free, and that the tool returns who receives details, consent wording, and confirmation method. This gives a clear and honest picture of the tool's behavior and consequences.
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 short, front-loaded with the most important instruction ('Read first'), and every sentence adds substantive value. It avoids filler while covering the core behavioral guarantees and 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 informational tool, the description is complete. It explains what the tool does, the context in which it should be read, the key caveats (free, no purchase, no guaranteed quote), and what information the returned description will contain.
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 there is nothing to document beyond the empty schema. The description appropriately focuses on the output content instead, which is the relevant semantic information for this informational 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 clearly states the tool's purpose: it describes what submit_enquiry does for CCTV Installation Cost, including that it starts an enquiry with human providers who quote directly. It also lists what the description returns, so an agent can confidently distinguish this informational tool from the action-oriented sibling submit_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' gives an explicit cue that this tool should be consulted before acting, and the description clarifies that it explains submit_enquiry. It doesn't explicitly contrast with enquiry_fields, but the use case is clear enough for an agent to know when to call this tool.
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 CCTV Installation 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 the full burden of behavioral disclosure. It clearly states what the tool exposes and even notes that allowed options are included 'where there are any.' It does not mention response format or side effects, but for a zero-parameter read-only metadata query, this is largely sufficient.
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 tight sentences with no filler. The first sentence front-loads what data the agent will receive, and the second provides a concrete workflow connection. Every clause earns its place.
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 tool with no output schema, the description covers the essential information: which enquiry, what fields are returned, and how to use the keys downstream. An explicit statement of the response format would make it fully complete, but the current text is adequate for an agent to invoke it 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 tool has no parameters, so the baseline is 4 under the rubric. The description adds value beyond that by explaining the meaning of field keys and how they should be used when calling submit_enquiry. There are no parameter details needed beyond this.
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 ('CCTV Installation Cost enquiry') and enumerates the exact data returned: key, label, type, required, help text, and options. The lack of an explicit verb like 'list' or 'return' is minor because 'Every field of...' unambiguously conveys the operation. It also partially distinguishes itself from submit_enquiry by describing how to use its output, though it does not differentiate 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 description implies usage by telling the agent to pass answers to submit_enquiry keyed by field key, which suggests enquiry_fields is the prerequisite for submission. However, it does not explicitly state when to use this tool versus enquiry_describe or when not to use it. The guidance is present but only implied, not explicit.
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 CCTV Installation 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 local CCTV installers, 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 local CCTV installers, 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 carries the full burden and does so thoroughly. It discloses that Step 1 only validates and returns a summary, consent line, and token, while Step 2 actually submits and triggers an email with a click-link before providers see anything.
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 longer than average but every sentence earns its place: the non-purchase clarification is front-loaded, and the two-step protocol is clearly labeled. It avoids fluff and uses the consent wording exactly where it matters.
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-step mutation tool with no output schema and no annotations, the description is complete. It covers the workflow, required consent, the token handoff, the email side effect, and the condition for providers to see the enquiry, leaving little ambiguity for an agent.
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?
Although schema coverage is 100%, the description adds important workflow meaning beyond the raw parameter definitions. It explains that answers must come keyed by enquiry_fields, that the same answers are reused in Step 2, and that the confirmation token is the link between the two calls.
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 action and resource: 'Submits an enquiry to CCTV Installation Cost' and immediately distinguishes what it is not ('NOT a purchase, NOT a guaranteed quote'). It also differentiates from siblings by presenting submit_enquiry as the submission step and referencing enquiry_fields as the source of answer keys.
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 gives explicit step-by-step usage: Step 1 requires answers and consent=true and returns a token; Step 2 is only used if the person agrees and must include the token. It also states the enquiry is not a purchase and not a guaranteed quote, which helps the agent avoid misuse.
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 role: enquiry_describe explains the process, enquiry_fields provides the schema, and submit_enquiry performs the actual submission. There is no overlap or ambiguity between them.
All names are snake_case and clearly reference the enquiry domain, but the pattern is slightly mixed: enquiry_describe and enquiry_fields put the noun first, while submit_enquiry puts the verb first. The names remain readable and predictable enough, but the ordering is not fully consistent.
Three tools is exactly right for this simple enquiry workflow: one for orientation, one for field definitions, and one for submission. Each tool earns its place and the server is well-scoped.
The tool set fully covers the enquiry lifecycle: understanding the process, retrieving the required fields, and submitting with confirmation. There are no obvious dead ends for an agent guiding a user through the enquiry flow.