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Glama
somusathya

connected-car-mcp

by somusathya

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
list_vehiclesA

List every vehicle in the fleet with its first/last telemetry timestamp.

get_vehicle_telemetryA

Get raw telemetry readings for one vehicle, optionally bounded by an ISO-8601 start/end timestamp. Returns at most limit readings, most recent first within that window.

fleet_health_summaryA

Get a fleet-wide snapshot: latest reading per vehicle, fleet averages, and which vehicles currently have an active anomaly flag.

detect_anomaliesA

List rule-based anomalies (overheating, low battery, fault codes, harsh driving) across the fleet, or for a single vehicle_id if given.

get_maintenance_recommendationsB

Get prioritized maintenance recommendations for one vehicle, combining service-interval mileage with any active anomaly flags.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription
fleet_overview_resourceA standing resource (as opposed to an on-demand tool call) giving a fleet health snapshot -- useful for a client that wants fleet state in context without spending a tool call to fetch it.

TDQS

A3.8/5.0

Scored across 5 tools

Disambiguation5/5

Every tool targets a distinct concern: listing vehicles, retrieving raw telemetry, fleet-wide health snapshot, anomaly detection, and maintenance recommendations. The overlap between fleet_health_summary and detect_anomalies is minimal because one is a snapshot and the other is a detailed listing.

Naming Consistency4/5

Most tools follow a clear verb_noun pattern (list_vehicles, get_vehicle_telemetry, detect_anomalies, get_maintenance_recommendations). The exception is fleet_health_summary, which lacks a verb prefix, creating a minor inconsistency in the naming scheme.

Tool Count5/5

Five tools is well-scoped for a connected-car MCP, covering the core operations of vehicle listing, telemetry retrieval, fleet health, anomaly detection, and maintenance recommendations without redundancy or bloat.

Completeness4/5

The set covers the primary read/analysis workflows: listing vehicles, fetching raw data, summarizing health, detecting anomalies, and recommending maintenance. A minor gap is the lack of a tool for direct vehicle metadata (e.g., model, year), but this is not critical for the apparent monitoring/analytics purpose.

Maintenance

ActivityMaintained
ResponsivenessNo issues