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google-ai-history-mcp

google-ai-history-mcp

by travispflanz

Get Google Ai Chat

get_google_ai_chat

Fetches a complete Google AI conversation by chat ID, title, or direct URL, enabling you to review, continue, or reuse the chat.

Instructions

Retrieve a full Google AI conversation by chat ID, title, or direct URL.

Input Schema

NameRequiredDescriptionDefault
chat_idYes
login_timeout_secNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.4/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full behavioral burden and does little: 'Retrieve' implies a read, but nothing is said about authentication/browser login needs, though the undocumented login_timeout_sec parameter strongly implies a login flow. It also says nothing about failure modes for unknown chat IDs or size/truncation behavior.

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 tight sentence with no filler, leading with the verb and resource. Nothing is wasted, though brevity comes at the cost of the missing detail noted elsewhere.

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-value explanation is unnecessary, and the description adequately conveys the core lookup. The remaining gap is the undocumented login_timeout_sec and the undefined boundary with fetch_google_ai_chat_url.

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 must compensate. It adds real value by revealing that the required string chat_id accepts a chat ID, a title, or a direct URL, but it never explains login_timeout_sec (default 45), so one of only two parameters remains fully opaque.

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?

Names a specific verb and resource ('Retrieve a full Google AI conversation'), which is clearer than the tautological title. However, it does not distinguish itself from the sibling fetch_google_ai_chat_url, and claiming it can retrieve by 'direct URL' directly overlaps with that sibling's apparent purpose.

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 in that it accepts three lookup key forms (ID, title, URL), which hints at when it applies. But it gives no explicit when-to-use versus list_google_ai_chats, search_google_ai_chats, or fetch_google_ai_chat_url, leaving the agent to guess which retrieval tool to pick.

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