UK/EU and international car transport quotes with HMRC, IVA, DVLA and logistics costings.
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Average 4.4/5 across 3 of 3 tools scored.
Each tool has a clearly distinct purpose: generate finalizes, get_requirements checks, update_draft modifies. No overlap.
Naming is inconsistent: 'quote_generate' is noun_verb, while 'quote_get_requirements' and 'quote_update_draft' are noun_verb_noun. No uniform pattern.
Three tools is appropriate for a focused connector covering the core workflow of updating, checking, and finalizing a quote.
Covers update, check, and finalize, but lacks a tool to create an initial draft or to list/delete quotes, causing minor gaps.
quote_generateGenerate quoteAInspectUse this after the user explicitly confirms a complete ShipMyCar quote draft. It calculates pricing, writes a private quote continuation/API usage record, and returns a continueQuoteUrl. It does not send email or create a public booking.
| Name | Required | Description | Default |
|---|---|---|---|
| draft | Yes | Complete MCP quote draft. | |
| confirm | Yes | Must be true to generate the quote. | |
| contactConsent | No | Set true only when the user consents to storing supplied contact details in the continuation payload. |
| Name | Required | Description |
|---|---|---|
| code | No | |
| draft | Yes | |
| quote | No | |
| status | No | |
| details | No | |
| message | No | |
| success | Yes | |
| requirements | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description details side effects (calculates pricing, writes record, returns URL) and clearly states what it does NOT do. Annotations show readOnlyHint=false, destructiveHint=false, consistent with writing a record. Provides context beyond annotations.
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 sentences, no wasted words. First sentence covers purpose and timing, second covers exclusions. Highly efficient and easy to parse.
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 3 parameters, present siblings, and existing output schema, the description covers purpose, usage timing, behavior, and limitations comprehensively. No gaps noted.
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?
All 3 parameters have schema descriptions (100% coverage). Description adds context about 'complete draft' and consent requirement but does not significantly enhance parameter meaning beyond the schema. Adequate baseline given 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?
Description clearly states verb 'generate' on resource 'quote' with specific context 'after user explicitly confirms a complete ShipMyCar quote draft'. Distinguishes from sibling tools (quote_get_requirements, quote_update_draft) by focusing on final generation step.
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?
Explicitly instructs when to use: after explicit user confirmation of a complete draft. Also states what it does not do (no email, no booking). Lacks explicit exclusions for other scenarios, but positive guidance is strong.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
quote_get_requirementsGet quote requirementsAUse this when a ShipMyCar quote draft needs checking before generation. It only inspects the draft and returns route requirements, enabled services, missing fields, and next questions.
| Name | Required | Description | Default |
|---|---|---|---|
| draft | Yes | Current MCP quote draft to inspect. |
| Name | Required | Description |
|---|---|---|
| draft | Yes | |
| success | Yes | |
| warnings | Yes | |
| routeType | Yes | |
| capability | Yes | |
| missingFields | Yes | |
| nextQuestions | Yes | |
| readyForQuote | Yes | |
| enabledRouteTypes | Yes | |
| enabledServiceModules | Yes | |
| requiredServiceModules | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only and non-destructive; description adds that it 'only inspects' and details the return content (route requirements, enabled services, missing fields, next questions), providing rich behavioral context without contradiction.
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 sentences, no wasted words, front-loaded with usage instruction and clear listing of return items.
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 presence of output schema, the description still covers purpose, usage, and key return elements. For a simple tool with one parameter and supportive annotations, this is complete.
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 has 100% coverage with a clear description of the single 'draft' parameter. The tool description does not add additional meaning beyond what the schema already provides, so baseline score of 3 is appropriate.
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 inspects a quote draft and returns specific requirements, with a verb and resource that distinguishes it from siblings like quote_generate and quote_update_draft.
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?
Explicitly says when to use ('when checking before generation') and implies read-only, but does not explicitly state when not to use it or name alternatives beyond sibling listing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
quote_update_draftUpdate quote draftAUse this when a user provides or corrects ShipMyCar quote details. It returns a stateless draft plus next questions and does not create records, send email, or contact ShipMyCar.
| Name | Required | Description | Default |
|---|---|---|---|
| draft | No | Current MCP quote draft returned by a previous tool call. | |
| patch | Yes | New quote details collected from the user. |
| Name | Required | Description |
|---|---|---|
| draft | Yes | |
| success | Yes | |
| warnings | Yes | |
| routeType | Yes | |
| capability | Yes | |
| missingFields | Yes | |
| nextQuestions | Yes | |
| readyForQuote | Yes | |
| requiredServiceModules | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond readOnlyHint annotation, the description clarifies statelessness, no record creation, no email, no contact, adding useful behavioral context.
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 sentences, no redundancy, front-loaded with usage condition, every sentence adds value.
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 annotations, full schema coverage, and output schema existence, the description sufficiently covers purpose, usage, and behavioral details for this low-complexity 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?
Schema coverage is 100% with parameter descriptions; the tool description adds no extra parameter meaning beyond what schema already provides.
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 action (updating draft) and resource (quote details), and specifies what the tool does and does not do, differentiating it from potential sibling tools like quote_generate.
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?
Explicitly says when to use ('when user provides or corrects quote details') but does not provide when-not-to-use or mention sibling alternatives directly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
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
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.
No comments yet. Be the first to start the discussion!