chrome-bridge-mcp

by deng1986

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JavaScript

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google_ai_ask

Send follow-up prompts to an ongoing Google AI conversation and read the updated response.

Instructions

Send a follow-up prompt to an existing Google AI Mode tab and read the updated conversation.

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": {
      "prompt": "<prompt>"
    },
    "name": "google_ai_ask"
  }
}

Input Schema

Name	Required	Description
`prompt`	Yes	Follow-up prompt to send.
`tabId`	No	Google AI Mode tab id. Defaults to the first page tab.
`timeoutMs`	No	Maximum time to wait for the conversation to change.
`maxChars`	No	Maximum visible conversation text characters to return.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jun 23, 2026

TDQS

B3.1/5.0

Behavior3/5

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

No annotations are provided, so the description must cover behavioral traits. It mentions both sending a prompt and reading the conversation, but does not disclose details like side effects, waiting behavior, or required permissions.

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

Conciseness4/5

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

The description is a single, clear sentence with no extraneous words. It efficiently conveys the primary function.

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

Completeness2/5

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

Given no output schema and no annotations, the description should provide more detail on return values, behavior (e.g., does it wait for completion?), and the meaning of 'read the updated conversation.' It is insufficient for an AI agent to fully understand the tool's effects.

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 100%, so the tool already documents all parameters. The description adds minor context ('follow-up', 'existing') but no additional meaning beyond the schema.

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 clearly states the action (send a follow-up prompt) and resource (existing Google AI Mode tab) with a specific verb. However, it does not explicitly distinguish from sibling tools like continue_google_ai_session, which may serve a similar purpose.

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 on when to use this tool versus alternatives such as ask_ai_page or continue_google_ai_session. The description lacks context for prerequisites or when not to use it.

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