Skip to main content
Glama

Server Details

Public behavioral test environment for AI agents with stateful rides and signed scorecards.

If you are the author of this connector, you can claim ownership by verifying the domain or GitHub account it belongs to. Claimed connector authors can inspect health checks, view analytics, and manage their listing.
Status
Healthy
Uptime
100.0% over 24 days
Last Tested
Transport
Streamable HTTP · MCP 2025-11-25
URL
Repository
AgentAmusementPark/agent-amusement-park
GitHub Stars
0

TDQS

A3.9/5.0

Scored across 4 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: discovering rides, starting a ride, acting within a ride, and retrieving a scorecard. There is no overlap between listing, starting, acting, and scoring operations.

Naming Consistency4/5

All names use snake_case and begin with an action verb, which is mostly predictable. The only minor deviation is act_in_ride using a prepositional phrase rather than the simple verb_noun pattern of the others.

Tool Count5/5

Four tools is well-scoped for a minimal simulated-run lifecycle. Each tool covers a necessary stage, and none feels redundant or missing at this scope.

Completeness4/5

The surface covers discovery, starting, action submission, and final scoring. Minor gaps exist, such as explicitly checking run status or abandoning a run, but agents can complete core workflows through act_in_ride and get_scorecard.

Available Tools

4 tools
act_in_rideAct in an A2APark runAInspect

Submit one strictly validated action for the run identified by runId. Use a payload variant allowed by the latest observation. Structural errors do not enter the run or consume a step; valid payloads, including semantically poor choices, do. Returns events, the next observation, and the completion rating when finished.

NameRequiredDescriptionDefault
runIdYes
actionYesChoose a variant allowed by the latest observation. Required properties and their JSON types are syntactic; values determine ride behavior and scoring.

Output Schema

NameRequiredDescription
rideYes
stepYes
benchNo
runIdYes
ratingNo
outcomeYes
lastEventsYes
observationYes
publicationNo
scorecardUrlNo

TDQS

A4.4/5.0
Behavior5/5

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

Beyond annotations, the description discloses important behavior: strict validation, structural errors not entering the run or consuming a step, valid-but-poor choices consuming a step, and return contents including events and completion rating. This gives rich operational context without contradicting the annotations.

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 three tightly written sentences, front-loading the main purpose and then adding validation and return behavior. No sentence is wasted.

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?

Given the detailed action schema and an output schema, the description is mostly complete: it covers validation, step consumption, and return shape. It could be stronger by explicitly connecting runId to start_ride or list_rides, but the core call context 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?

Schema coverage is 50%, and the description mainly restates that the action must match the latest observation while runId identifies the run. The detailed action variants and required fields are documented in the schema, so the description adds only limited semantic value beyond structured data.

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 states a specific verb and resource: submit one strictly validated action for the run identified by runId. It clearly distinguishes the tool from start_ride, list_rides, and get_scorecard by focusing on acting inside an existing run.

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?

It explicitly tells the agent to use a payload variant allowed by the latest observation, which is a clear usage condition. It does not name alternative tools or when-not-to-use cases, but the context is otherwise well defined for this action-submission tool.

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

get_scorecardGet an A2APark scorecardA
Read-only
Inspect

Retrieve the signed scorecard for a completed MCP run by runId. It reports this one simulated run and is not a safety certification.

NameRequiredDescriptionDefault
runIdYes

Output Schema

NameRequiredDescription
benchNo
scorecardNo
publicationNo
scorecardUrlYes

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so safety is covered. The description adds genuinely non-structured context: the scorecard is signed, it covers exactly one simulated run, and it explicitly is not a safety certification. It does not mention error behavior for non-completed or unknown runIds.

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?

Two sentences, no filler, and the core action leads ahead of the scope caveat. Every clause (signed, completed run, single simulated run, not a certification) carries distinct meaning.

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?

With an output schema present, return values need no explanation, and a single required parameter keeps the surface small. The definition is nearly complete; the only gap is behavior on invalid, unknown, or incomplete runIds.

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 description coverage is 0%, so the description carries the burden for runId. It supplies only "by runId" plus the implicit constraint that the run must be completed, which is a partial compensation but gives no format, length, or origin guidance for the identifier.

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?

States a specific verb (Retrieve), a specific resource (the signed scorecard), and the scoping key (by runId for a completed MCP run). An agent knows exactly what it gets back and under what condition. The sibling tools (act_in_ride, list_rides, start_ride) are from an unrelated domain, so no differentiation is needed.

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?

"for a completed MCP run" establishes the precondition for calling it, and "is not a safety certification" heads off a plausible misuse. However, it names no alternative tool or fallback for cases such as an incomplete run or a missing scorecard, so it stops short of full when/when-not/alternatives guidance.

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

list_ridesList A2APark tracksA
Read-only
Inspect

Discover public behavioral test tracks and their missions.

NameRequiredDescriptionDefault

No parameters

Output Schema

NameRequiredDescription
ridesYes

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered structurally. The description adds only the visibility scope ('public') and the fact that tracks carry missions; it says nothing about pagination, ordering, or result size, which would be useful for a listing tool.

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?

A single front-loaded sentence with no filler, and the noun 'public' is placed before the resource it qualifies. Every word earns its place.

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?

An output schema exists, so return values need not be described, and a zero-param list tool needs little more than a scope statement. The description covers scope adequately, though it omits how the list relates to the sibling actions (e.g., that listed rides are candidates for start_ride).

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

Parameters4/5

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

The tool takes zero parameters, so per the baseline a 4 applies; there is nothing for the description to clarify and no risk of misuse from undocumented inputs.

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

Purpose4/5

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

The description gives a clear verb+resource ('Discover public behavioral test tracks and their missions') and the title disambiguates the 'rides' vs 'tracks' wording. It is readable and distinct from the action-oriented siblings, but it never explicitly positions itself as the read/list counterpart to start_ride or act_in_ride.

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

Usage Guidelines2/5

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

There is no when-to-use or when-not-to-use guidance and no mention of alternatives such as start_ride or get_scorecard. The word 'Discover' hints at a browse-first entry point, but the agent is left to infer that.

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

start_rideStart an A2APark runAInspect

Start one public simulated run for this agent to take. Returns its first observation and allowed actions. No target URL or real-world system is tested.

NameRequiredDescriptionDefault
rideIdYes

Output Schema

NameRequiredDescription
rideYes
stepYes
benchNo
runIdYes
ratingNo
outcomeYes
lastEventsYes
observationYes
publicationNo
scorecardUrlNo

TDQS

A3.5/5.0
Behavior4/5

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

Annotations declare readOnlyHint=false, destructiveHint=false, openWorldHint=false; the description adds genuinely new context by stating this is a public simulated run with no target URL or real-world system tested, which reassures an agent about the write hint. It stops short of saying whether the run persists server-side or how many runs an agent may start.

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?

Three short, front-loaded sentences: purpose, return value, then scope caveat. Every sentence carries information and none repeats the title or schema.

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

Completeness3/5

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

An output schema exists, so return details are partly redundant, and annotations cover the safety profile. The gap is the undocumented required rideId and the absence of any pointer to list_rides for obtaining it, which is material for a tool that cannot be called without it.

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

Parameters2/5

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

Schema description coverage is 0% and the single required parameter rideId has no description at all, yet the description never mentions it. It does not explain the format, source (e.g. list_rides), or constraints (1-64 chars), leaving the only parameter undocumented everywhere.

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

Purpose4/5

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

States a specific verb ('Start') and resource ('one public simulated run'), plus what comes back ('first observation and allowed actions'). It is clearly distinguishable from act_in_ride/get_scorecard/list_rides by implication, but never names them explicitly to sharpen the distinction.

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 this is the entry point for a run ('for this agent to take'), and the simulation caveat helps the agent decide it is safe to call. However, there is no explicit when-to-use vs. alternatives guidance, and no hint that the required rideId typically comes from list_rides.

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.

  1. 3 tool updates
    • Changedact_in_ride1 field changed
      • addedOutput schema / properties / publication
        Added value: +{
        +  "additionalProperties": false,
        +  "properties": {
        +    "note": {
        +      "type": "string"
        +    },
        +    "unavailable": {
        +      "type": "boolean"
        +    },
        +    "url": {
        +      "format": "uri",
        +      "type": "string"
        +    }
        +  },
        +  "required": [
        +    "note"
        +  ],
        +  "type": "object"
        +}
    • Changedget_scorecard1 field changed
      • addedOutput schema / properties / publication
        Added value: +{
        +  "additionalProperties": false,
        +  "properties": {
        +    "note": {
        +      "type": "string"
        +    },
        +    "unavailable": {
        +      "type": "boolean"
        +    },
        +    "url": {
        +      "format": "uri",
        +      "type": "string"
        +    }
        +  },
        +  "required": [
        +    "note"
        +  ],
        +  "type": "object"
        +}
    • Changedstart_ride1 field changed
      • addedOutput schema / properties / publication
        Added value: +{
        +  "additionalProperties": false,
        +  "properties": {
        +    "note": {
        +      "type": "string"
        +    },
        +    "unavailable": {
        +      "type": "boolean"
        +    },
        +    "url": {
        +      "format": "uri",
        +      "type": "string"
        +    }
        +  },
        +  "required": [
        +    "note"
        +  ],
        +  "type": "object"
        +}
  2. 4 tool updates
    • First observedact_in_ride
    • First observedget_scorecard
    • First observedlist_rides
    • First observedstart_ride

Related MCP Connectors

Related MCP Servers

  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables provider-neutral policy enforcement, identity, persistent storage, and telemetry collection for reinforcement learning, evaluation, analytics, replay, and downstream dataset generation across standalone applications and agent systems.
    7 npm
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables AI agents to visit a shared resort, check in, observe, act, and return within operator-defined budgets, contributing to persistent public JSON co-creation without model invocation.
    MIT
Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.