NotebookLM MCP Server

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

No annotations are provided, so the description carries full burden. It discloses key behavioral traits: it's a read operation ('Get'), returns raw text without AI processing, and is performance-optimized ('Much faster'). However, it doesn't mention error conditions, rate limits, authentication needs, or what happens with invalid source IDs, leaving some behavioral aspects unclear.

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

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

Perfectly structured and front-loaded: first sentence states purpose, second explains scope, third gives performance comparison. The Args/Returns section is cleanly separated. Every sentence earns its place with zero wasted words.

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

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

Given 1 parameter with 0% schema coverage and an output schema (implied by Returns section), the description does well: it explains the parameter, lists return values, and provides usage context. However, it doesn't mention authentication requirements or error handling, which could be important for a tool accessing potentially sensitive content.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

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 provides the parameter name ('source_id') and clarifies it's a 'Source UUID', adding semantic meaning beyond the bare schema. However, it doesn't explain where to find source IDs or provide format examples, leaving some practical usage gaps.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Get raw text content') and resource ('of a source'), specifying it returns original indexed text from specific formats (PDFs, web pages, etc.) and distinguishes it from sibling 'notebook_query' by noting it's faster for content export. This provides specific differentiation from alternatives.

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

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

Explicitly states when to use this tool ('Much faster than notebook_query for content export') and when not to use it ('no AI processing'), providing clear alternatives and context. This gives the agent precise guidance on tool selection.

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