notebooklm-mcp

Overview Schema Source Related Servers Discussions Admin

source_get_content

Retrieve the extracted text and metadata of a specific source from a NotebookLM notebook. Provide the notebook ID and source ID to access the source's content.

Instructions

Return the extracted text/metadata of a single source.

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": {
      "notebook_id": "<notebook_id>",
      "source_id": "<source_id>"
    },
    "name": "source_get_content"
  }
}

Input Schema

Name	Required	Description	Default
`source_id`	Yes
`notebook_id`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0Aug 2, 2026

TDQS

B3.2/5.0

Behavior2/5

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

With no annotations provided, the description must bear all responsibility for behavioral disclosure. It only says 'Return' with no mention of potential errors (e.g., missing source, permissions) or any side effects. While it implies a read operation, it does not explicitly state that it is non-destructive or requires existing data.

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 a single, efficient sentence with no wasted words. It front-loads the action and object, making it easy to parse.

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?

The tool is simple (2 parameters, output schema exists), so the description is arguably sufficient for the core purpose. However, it lacks any usage context, such as when to use this against notebook_query or source_add, and does not mention any behavioral prerequisites (e.g., source already processed). This makes it minimally viable but not complete.

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

Parameters2/5

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 does not explain 'source_id' or 'notebook_id' beyond their names, nor how they relate. For a tool with two self-explanatory parameters, this is acceptable but still lacks semantic context (e.g., that source_id is scoped by notebook_id).

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 returns extracted text/metadata of a single source, using a specific verb ('Return') and resource ('source'). This distinguishes it from sibling tools like source_add (which adds sources) and source_sync_drive (which syncs drive content).

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 does not mention prerequisites (e.g., source must be added first) or compare it to sibling tools like source_add or source_sync_drive. This is a clear gap for an agent deciding between related source tools.

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