Skip to main content
Glama
set2374

NotebookLM MCP Server

by set2374

chat_configure

Configure chat settings for NotebookLM notebooks by setting goals, custom prompts, and response lengths to tailor AI interactions.

Instructions

Configure notebook chat settings.

Args: notebook_id: Notebook UUID goal: default|learning_guide|custom custom_prompt: Required when goal=custom (max 10000 chars) response_length: default|longer|shorter

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notebook_idYes
goalNodefault
custom_promptNo
response_lengthNodefault

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'Configure' which implies a mutation/write operation, but doesn't disclose whether this requires specific permissions, if changes are reversible, what happens to existing settings, or any rate limits/constraints. The description adds minimal behavioral context beyond the basic action.

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 efficiently structured with a clear purpose statement followed by a well-organized Args section. Every sentence earns its place - the first sentence states the tool's purpose, and the Args provide essential parameter information without redundancy. The information is front-loaded and appropriately sized.

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?

Given that there's an output schema (which means return values are documented elsewhere), the description covers the basic purpose and parameters adequately. However, for a configuration/mutation tool with no annotations, it should provide more behavioral context about permissions, side effects, and constraints. The parameter documentation is good, but overall completeness is moderate for a tool that modifies system settings.

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 description provides meaningful parameter documentation in the Args section, explaining each parameter's purpose and constraints (e.g., 'Required when goal=custom', 'max 10000 chars', enum values like 'default|learning_guide|custom'). With 0% schema description coverage, this compensates well for the schema's lack of descriptions, though it doesn't cover all possible semantic nuances.

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 verb ('Configure') and resource ('notebook chat settings'), making the purpose specific and understandable. However, it doesn't explicitly differentiate this tool from its siblings (e.g., notebook_describe, notebook_get), which are read operations while this appears to be a configuration/mutation tool. The purpose is clear but lacks sibling differentiation.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., notebook must exist), when-not-to-use scenarios, or how it relates to sibling tools like notebook_describe or notebook_get. The Args section documents parameters but doesn't offer usage context.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/set2374/notebooklm-mcp-archived'

If you have feedback or need assistance with the MCP directory API, please join our Discord server