Skip to main content
Glama
trustcarinfo

mcp-server-trustcar

Official
by trustcarinfo

mcp-server-trustcar

MCP (Model Context Protocol) server for trustcar.info — a Ukrainian licence-plate lookup and driver review service. Ask your AI assistant "что за машина AA1234BC?" and it will answer with the registration region, vehicle make/model/year, community rating and recent reviews.

This package is a thin stdio bridge to the site's native MCP endpoint (https://trustcar.info/mcp). Tools are discovered at startup, so the package never goes stale.

Tools

Tool

Description

Auth

lookup_plate

Region, vehicle (make/model/year/fuel), rating and recent reviews for a Ukrainian licence plate

none

recent_plates

Recently active plates on trustcar.info (with vehicle make/model where known)

none

post_review

Post a licence-plate review on behalf of an authenticated user (labelled as AI-agent-generated, shown separately, does not affect the community rating)

OAuth bearer

Related MCP server: Consulta Veicular Estadual

Install

Claude Code

claude mcp add trustcar -- npx -y mcp-server-trustcar

Claude Desktop

{
  "mcpServers": {
    "trustcar": {
      "command": "npx",
      "args": ["-y", "mcp-server-trustcar"]
    }
  }
}

Cursor / Windsurf / other MCP clients

Any client that speaks stdio MCP works the same way: command npx, args -y mcp-server-trustcar.

Remote (no install)

MCP clients that support remote servers can skip this package entirely and connect straight to:

https://trustcar.info/mcp

Configuration

Env var

Meaning

TRUSTCAR_MCP_URL

Override the endpoint URL (default https://trustcar.info/mcp)

TRUSTCAR_TOKEN

OAuth bearer token — only needed for post_review. Discovery: /.well-known/oauth-protected-resource

Example

User: Что за машина AA1234BC?

Assistant: (calls lookup_plate) AA1234BC is registered in Kyiv (AA region). It's a Toyota Camry, 2019, petrol. Community rating on trustcar.info: 4/5 from 3 reviews, the latest one mentions polite driving…

Development

npm install
npm run build
npm test

License

MIT © trustcar.info

Available Tools

3 tools
lookup_plateAInspect

Look up a Ukrainian licence plate on trustcar.info: region, vehicle (make/model/year/fuel), rating and recent reviews.

ParametersJSON Schema
NameRequiredDescriptionDefault
plateYesPlate number, e.g. AA1234BB

TDQS

A4.1/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It implies a read-only lookup operation and names the external site, but it does not disclose potential error conditions, network dependencies, or rate limits. The description is adequate but does not go beyond basic expectations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence that efficiently conveys purpose and output fields without redundancy. Every phrase earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with one parameter and no output schema, the description fully covers what the tool does and what it returns (region, vehicle details, rating, reviews). The external source is specified. This is complete for a simple lookup operation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% for the single 'plate' parameter, which already includes a format description and example. The tool description adds no semantically new parameter information, keeping it at the baseline 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the specific verb 'Look up' and names the resource ('Ukrainian licence plate') and source ('trustcar.info'), listing the returned data (region, vehicle, rating, reviews). This clearly distinguishes it from siblings: recent_plates (listing) and post_review (writing).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not explicitly state when to use this tool instead of recent_plates or post_review, but the read/lookup intent is clear from the verb and data fields. The context is sufficient, but it lacks explicit exclusion statements.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

post_reviewAInspect

Post a licence-plate review on behalf of the authenticated user. Requires an OAuth access token with the "write" scope (discover via /.well-known/oauth-protected-resource). The review is labelled AI-agent-generated, shown in a separate section, and does NOT affect the human rating.

ParametersJSON Schema
NameRequiredDescriptionDefault
textYesReview text (min 3 chars)
plateYesPlate number, e.g. AA1234BB
ratingYesStar rating 1-5

TDQS

A4.4/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden and reveals several non-obvious behaviors: OAuth scope discovery, AI-agent-labelled output, separate section, and no impact on the human rating. This goes well beyond what the input schema provides.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the action, and followed by necessary authentication and behavioral caveats. Every sentence earns its place with no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple 3-parameter write operation with no output schema, the description explains purpose, authentication, and the special output treatment. It does not mention response/error details, but the essential context for safe and correct use is present.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema covers all three parameters (plate, rating, text) with descriptions, achieving 100% schema coverage. The description adds no additional parameter-level meaning, so a baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description begins with 'Post a licence-plate review', a specific verb+resource action. It clearly distinguishes from the sibling read tools (lookup_plate, recent_plates) by focusing on the write/submission operation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly states the authenticated-user requirement and OAuth 'write' scope, giving the context for when this tool applies. It does not explicitly name alternatives or when-not-to-use, but the sibling read tools make the write-vs-read distinction obvious.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

recent_platesAInspect

List recently active plates on trustcar.info (with vehicle make/model where known).

ParametersJSON Schema
NameRequiredDescriptionDefault
limitNo1-50, default 12

TDQS

A4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the burden. It discloses the read-only nature via 'List' and adds the useful caveat that vehicle make/model are included only where known, setting expectations for the output.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

One sentence, front-loaded with the main action, and includes a relevant qualifier without waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple list tool with a single optional parameter, the description provides enough context for invocation: it names the data source, the type of items, and an output detail. The absence of an output schema is mitigated by the straightforward nature of the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already documents the limit parameter with range and default (100% coverage), so the description need not elaborate; it adds no additional meaning for parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the specific verb 'List' with the resource 'recently active plates' on trustcar.info, clearly distinguishing from siblings lookup_plate and post_review.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for listing recent plates but does not explicitly contrast with lookup_plate or post_review, leaving the when-to-use decision to inference.

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.

  1. 3 tool updatesv1.0.2
    • First observedlookup_plate
    • First observedpost_review
    • First observedrecent_plates

TDQS

A4.2/5.0
Disambiguation5/5

Each tool targets a clearly distinct action: lookup retrieves a single plate's details, recent lists plates, and post creates a review. There is no overlap or ambiguity between them.

Naming Consistency4/5

Two tools use verb_noun (lookup_plate, post_review) but recent_plates uses adjective_noun, deviating from the pattern. The names are still intuitive and readable.

Tool Count5/5

Three tools is well-scoped for a niche service focused on licence plate lookup, listing, and review posting. Each tool serves a distinct need without excess.

Completeness4/5

The core read and write operations are covered: lookup provides full details and reviews, recent lists plates, and post creates a review. Minor gaps like updating or deleting reviews are not essential for the server's purpose.

Maintenance

ActivityMaintained
ResponsivenessSyncing

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Connectors

Related MCP Servers

  • A
    license
    Not graded
    quality
    D
    maintenance
    MCP server for structured public vehicle data from StartMyCar, providing tools to list makes, models, problems, reviews, fuse box data, manuals, guides, and compare models.
    15
    MIT
  • A
    license
    Not graded
    quality
    C
    maintenance
    MCP server that enables querying Brazilian vehicle data by plate, returning details like brand, model, year, and color. It is read-only, hosted, and works with any MCP client over HTTP.
    MIT

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/trustcarinfo/mcp-server-trustcar'

If you have feedback or need assistance with the MCP directory API, please join our Discord server