Server Details
Conveyancing Fees Australia: the site's own MCP server — enquiry (enquiry = a human handoff, not...
- 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 Conveyancing Fees Australia: 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. It discloses the non-transactional nature ('Nothing is bought, ordered or paid'), the free nature, the lack of guarantee ('no quote is guaranteed'), and what the tool returns (who receives details, consent wording, confirmation method). This is thorough and accurate.
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 three sentences, front-loaded with a clear directive ('Read first'), and every clause contributes meaningful information. There is no filler or 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?
For a zero-parameter informational tool with no output schema, the description is complete: it states what the tool does, what it does not do, what the user should expect, and what content is returned. No critical gaps remain.
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 for the description to add beyond the schema. The baseline of 4 applies because parameter semantics are not a concern.
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 ('States plainly') and resource ('what submit_enquiry does on Conveyancing Fees Australia'), and makes clear this tool is explanatory, not transactional. It differentiates itself from submit_enquiry by emphasizing that nothing is bought, ordered, or paid.
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?
'Read first' gives explicit timing guidance: this should be used before taking action, likely before submit_enquiry. It does not mention enquiry_fields or give explicit 'when not to use' alternatives, but the context is clear enough.
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 Conveyancing Fees Australia 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?
There are no annotations, so the description carries the full behavioral burden. It describes what the tool returns and the structure of that data, and it clearly indicates a read-only discovery operation. However, it does not mention response format, error behavior, or that the tool takes no arguments, leaving some behavior implicit.
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 long, front-loaded with the exact contents of the response, and ends with a useful routing hint for submit_enquiry. Every sentence earns its place, and the title reinforces the purpose without redundancy.
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 and no output schema, the description provides enough context: what the tool returns, the field attributes, and how to use the result with submit_enquiry. It could mention the absence of required arguments or clarify the difference from enquiry_describe, but these are minor gaps for such a simple metadata 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?
The tool has zero parameters, and the schema already documents that with an empty properties object. The baseline for zero-parameter tools is 4, and the description adds no contradictory or missing parameter information. It appropriately focuses on the response contents instead.
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 tool's resource: every field of the Conveyancing Fees Australia enquiry, including key, label, type, required status, help text, and allowed options. It distinguishes itself from the sibling submit_enquiry by explaining that answers should be passed to that tool keyed by these field keys, though it does not explicitly contrast with 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 gives practical usage context by stating that answers should be passed to submit_enquiry using the field keys returned here. This implies the tool should be used to discover the enquiry schema before submission, though it does not explicitly state when to choose this over enquiry_describe.
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 Conveyancing Fees Australia — 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 licensed conveyancers or property solicitors in my state, 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 relevant licensed conveyancers or property solicitors in my state, 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 available, the description fully carries the transparency burden. It discloses validation behavior, the step-1 return artifacts (summary, consent line, confirmation token), the requirement for the person's agreement before step 2, and the side effect that the person must click an emailed link before any provider sees the enquiry.
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 well-structured as Step 1 and Step 2, with the non-purchase disclaimer upfront. The only notable redundancy is repeating the exact consent wording that already appears in the schema, which adds length without new information.
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 no output schema, the description does a strong job: it covers the two call variants, required inputs, step-1 return values, and the post-submission email-link behavior. The main gap is that it does not describe the step-2 return value or any error/edge-case behavior, but the tool remains usable from the description alone.
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: answers must be keyed per enquiry_fields, consent=true must accompany the exact quoted agreement, and the confirmation parameter is the step-1 token reused in step 2. This is helpful context beyond the already clear schema property descriptions.
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 opens with a specific verb and resource: 'Submits an enquiry to Conveyancing Fees Australia' and immediately excludes misuse by saying it is NOT a purchase or guaranteed quote. It also references the sibling tool enquiry_fields as the source of answer keys, helping to distinguish the submission action from companion tools.
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 an explicit two-step protocol: call with answers and consent=true, show the summary and consent line, then call again with the confirmation token only if the person agrees. It states key exclusions (not a purchase, not a guaranteed quote), but it does not explicitly say when to choose enquiry_describe or enquiry_fields over this tool.
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
Frequently Asked Questions
Claiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as
io.github.alice/server, link the matching GitHub user, then choose Claim with GitHub. An organization namespace such asio.github.acme/serveralso needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at
/.well-known/glama.jsonon the same origin as the connector, then choose Check HTTP challenge.DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
Discussions
No comments yet. Be the first to start the discussion!
Related MCP Connectors
Conveyancing Fees NZ: the site's own MCP server — enquiry (enquiry = a human handoff, not a...
31Conveyancing Fees Ireland: the site's own MCP server — enquiry (enquiry = a human handoff, not a...
Compare My Conveyancing: the site's own MCP server — compare, enquiry (enquiry = a human...
61Underpinning Costs: the site's own MCP server — enquiry (enquiry = a human handoff, not a...
Related MCP Servers
- FlicenseAqualityBmaintenanceMCP server for querying Australian modular housing regulations, including granny flat rules by state and council, with cross-jurisdiction comparison and data freshness checks.3-
- AlicenseNot gradedqualityDmaintenanceMCP server for qualifying and responding to inbound leads in seconds using a multi-agent AI pipeline.1MIT
- FlicenseNot gradedqualityBmaintenanceProvides comprehensive Australian planning property reports, including zoning, overlays, land size, and utility information for AI assistants. This high-performance MCP server is built for Cloudflare Workers and enables real-time property data retrieval through an HTTP-based interface.-
- AlicenseAqualityBmaintenanceUK due diligence MCP server — Companies House, corporate research, compliance checks193MIT
Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
Each tool has a distinct responsibility: one explains the process, one provides the field schema, and one performs the submission. There is no meaningful overlap or boundary ambiguity.
The names are readable and share the 'enquiry' root, but the pattern is inconsistent: enquiry_describe and enquiry_fields use a noun-first structure while submit_enquiry uses verb-first. This creates minor style inconsistency without losing meaning.
Three tools is well-scoped for a single enquiry submission workflow. It avoids bloat while providing the necessary orientation, schema, and submission functions.
The set fully covers the enquiry lifecycle: describing the process, obtaining valid fields, and submitting with consent and confirmation. No obvious gap exists for the stated purpose.