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dougrn

NotebookLM MCP Server

by dougrn

Source Read

source_read
Read-only

Read a NotebookLM source at summary or full detail to triage sources or inspect extracted content by notebook/source name or ID.

Instructions

Read a source at one of two detail levels. Accepts a notebook/source name or ID.

detail selects what you get back (two distinct shapes):

  • summary — a tiny AI digest for low-token triage: {notebook_id, source_id, summary, keywords}. Cheap to fan out across many sources before deciding which to pull in full.

  • full (DEFAULT) — the source metadata (incl. kind/status_label/ drive_status_label) plus the extracted content, the full char_count, and a truncated flag. content is ALWAYS bounded: omitting max_chars caps it at the first 10,000 chars; raise max_chars and/or page with offset (slice [offset : offset+max_chars]). char_count stays the FULL length. content is null (char_count 0) when the source isn't ready yet or has no extractable text.

output_format (text default / markdown, needs the server's markdownify extra) and max_chars / offset apply only to detail="full" (ignored for summary). Prefer chat_ask for querying large sources rather than pulling the whole body.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
detailNofull
offsetNo
sourceYes
notebookYes
max_charsNo
output_formatNotext

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, yet the description adds substantial behavior: content is ALWAYS bounded at 10,000 chars by default, char_count stays full length, content is null (char_count 0) when the source isn't ready, and markdown output needs the server's markdownify extra. These are non-obvious traits an agent needs to avoid misreading results.

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?

Long but front-loaded (the purpose is the first clause) and organized with bullets separating the two shapes. Density is justified by 6 parameters at 0% schema coverage, though a couple of parenthetical asides could be trimmed.

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

Completeness5/5

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

For a 6-param tool with no output schema and no schema descriptions, the description covers return shapes, bounding/truncation, readiness edge cases, and the sibling routing. Nothing required to invoke it correctly is missing.

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

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description carries the full burden and does: it gives the exact return shape for each detail value, explains max_chars/offset as the slice [offset : offset+max_chars], notes offset is ignored for summary, and states notebook/source accept name or 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?

States a specific verb+resource ('Read a source') and immediately scopes it with 'one of two detail levels,' which distinguishes it from source_list (listing), source_add (writing), and chat_ask (querying). An agent can separate it from every sibling without opening a schema.

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?

Explicitly routes on detail level ('summary' for low-token triage fan-out, 'full' for the body) and names the alternative for large sources: 'Prefer chat_ask for querying large sources rather than pulling the whole body.' This is when-to-use plus an explicit alternative.

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