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Pantheon-Security

NotebookLM MCP Server (Security Hardened)

Health Check

get_health
Read-onlyIdempotent

Check server health status, authentication state, and active sessions to verify readiness for research workflows. Use deep check mode to confirm NotebookLM chat UI accessibility.

Instructions

Get server health status including authentication state, active sessions, and configuration. Use this to verify the server is ready before starting research workflows.

Deep Check Mode (v2026.1.1) Set deep_check: true to actually verify the NotebookLM chat UI loads. This catches stale sessions where cookies exist but the UI won't load. Returns chat_ui_accessible: true/false.

If authenticated=false and having persistent issues: Consider running cleanup_data(preserve_library=true) + setup_auth for fresh start with clean browser session.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
deep_checkNoIf true, actually navigates to NotebookLM and verifies the chat UI loads. More reliable but slower (~5s). Use this before important query sessions.
notebook_idNoNotebook to check (for deep_check). Defaults to active notebook or first available.
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering basic safety. The description adds valuable behavioral context beyond annotations: the deep_check mode's performance impact ('slower (~5s)'), reliability benefits ('more reliable'), and specific return field ('chat_ui_accessible: true/false'). It also mentions authentication troubleshooting workflows, though it doesn't detail rate limits or exact error behaviors.

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 appropriately sized and front-loaded with the core purpose and usage. The deep_check section and troubleshooting advice are relevant but slightly verbose. Most sentences earn their place by providing actionable guidance, though the troubleshooting paragraph could be more concise.

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 tool's moderate complexity (health check with optional deep verification), rich annotations (readOnly, idempotent, non-destructive), and 100% schema coverage, the description is largely complete. It explains the tool's role in workflows, deep check behavior, and troubleshooting steps. The main gap is lack of output schema, but the description partially compensates by mentioning specific return fields like chat_ui_accessible.

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%, with both parameters well-documented in the schema. The description adds some context for deep_check ('actually navigates to NotebookLM and verifies the chat UI loads') and notebook_id ('Defaults to active notebook or first available'), but doesn't provide significant additional semantic meaning beyond what's already in the schema descriptions. This meets the baseline for high schema coverage.

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 clearly states the tool's purpose with specific verbs ('Get server health status') and resources ('authentication state, active sessions, and configuration'), distinguishing it from sibling tools like get_audio_status or get_video_status. It explicitly identifies what health information is returned, making the purpose unambiguous.

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

Usage Guidelines5/5

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

The description provides explicit guidance on when to use this tool ('to verify the server is ready before starting research workflows') and when to use alternatives (e.g., cleanup_data + setup_auth for authentication issues). It also distinguishes between normal and deep check modes, offering clear usage contexts.

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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