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AI CLI MCP Server

AI CLI MCP Server

by kiranmaya
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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antigravity_review

Run automated code reviews on a workspace using Google Antigravity CLI, returning critique and execution details. Provide optional custom instructions to focus the review.

Instructions

Performs an automated code review on a workspace using Google Antigravity CLI.

Args: working_directory: Root directory of the workspace or repository to review. instructions: Optional custom review criteria, guidelines, or focus areas. model: Optional model override. timeout: Execution timeout in seconds (default: 300).

Returns: JSON string containing review critique, exit code, and execution summary.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "working_directory": "<working_directory>"
    },
    "name": "antigravity_review"
  }
}

Input Schema

NameRequiredDescriptionDefault
modelNo
timeoutNo
instructionsNo
working_directoryYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the disclosure burden. It does state the tool executes an external CLI and returns a JSON string with critique, exit code, and summary, which is useful. However, it does not disclose whether the review is read-only, whether the Antigravity CLI must be pre-installed/authenticated, or what happens on timeout. These are meaningful gaps for a tool that invokes an external command.

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 compact and well-organized: a single purpose sentence followed by a short Args list and a one-line Returns format. Every sentence adds value, and the key information is front-loaded. No fluff or repetition.

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?

The presence of an output schema means return-value details are already covered, and the parameter semantics are provided. But for a CLI-invoking tool with no annotations, important context is missing: when to use this over sibling tools, prerequisites like CLI installation/auth, and whether the operation mutates the workspace. The description is adequate but not complete.

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?

Schema description coverage is 0%, so the description must compensate. The Args section gives meaningful semantics for all four parameters: 'working_directory' is clarified as the root of the workspace or repository, 'instructions' as custom review criteria, 'model' as an optional override, and 'timeout' with its default. The model override remains vague about available options, but this is a solid compensation given the schema provides no descriptions.

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 opens with a clear verb and resource: 'Performs an automated code review on a workspace using Google Antigravity CLI.' This distinguishes it from codex_review by naming Antigravity, and from antigravity_run through the 'review' verb. However, it doesn't explicitly call out any sibling by name, so differentiation is implied rather than stated.

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?

No guidance is given about when to use this tool versus siblings like codex_review or antigravity_run. The optional 'instructions' parameter hints at customization, but there is no explicit context, exclusion, or alternative recommendation. The agent is left to infer the appropriate use case.

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

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