| name | notebooklm-mcp-cli |
| description | Use when working with Google NotebookLM through jacob-bd/notebooklm-mcp-cli: listing or creating notebooks, adding sources, querying notebooks, generating audio or studio artifacts, revising slides, downloading artifacts, sharing notebooks, syncing Drive sources, running cross-notebook queries, configuring the NotebookLM MCP server, or diagnosing NotebookLM CLI authentication. Prefer this over generic Google or MCP skills when the task is specifically about NotebookLM. |
NotebookLM MCP CLI
Source
- Upstream repository:
https://github.com/jacob-bd/notebooklm-mcp-cli
- Local checkout:
%USERPROFILE%\.notebooklm-mcp-cli\notebooklm-mcp-cli
- Installed package:
notebooklm-mcp-cli
- CLI command:
nlm
- MCP server command:
notebooklm-mcp
- Universal stack source registry:
%USERPROFILE%\.universal-ai-stack\config\source-integrations.json
Operating Model
Use the CLI first. The MCP server is available for clients that require a live tool endpoint, but it should not be started or registered by default for simple one-shot NotebookLM work.
Do not copy this upstream repository, cookies, browser profiles, generated media, or NotebookLM session state into AI roots or into this repo. The universal install uses:
- the PyPI/uv tool install for executables,
- one external source checkout for README-grounded reference,
- this one canonical skill for routing and workflow instructions,
- compact
skill-router wrappers in each AI client.
Authentication
NotebookLM access depends on the user's Google account session.
Check auth before doing NotebookLM operations:
nlm login --check
If auth is missing, use the upstream login flow:
nlm login
For multiple Google accounts:
nlm login --profile work
nlm login --profile personal
nlm login profile list
nlm login switch work
Never print, paste, store, or commit browser cookies, Google OAuth state, downloaded private source files, or NotebookLM-generated private artifacts.
CLI Workflows
Use nlm --ai for the upstream's full AI-assistant command reference when exact syntax is needed.
Common commands:
nlm notebook list
nlm notebook create "Research Project"
nlm source add <notebook> --url "https://example.com/article"
nlm source add <notebook> --file "C:\path\source.pdf"
nlm notebook query <notebook> "What are the key findings?"
nlm cross query "Compare these notebooks on the main risks"
nlm studio create <notebook> audio --confirm
nlm download audio <notebook> <artifact-id>
nlm share public <notebook>
nlm doctor
Capabilities to prefer this skill for:
- notebook list/create/delete workflows,
- adding URL, text, Drive, and file sources,
- source-grounded notebook queries,
- cross-notebook research,
- batch query/create/delete operations,
- pipeline run/list workflows,
- tags and smart notebook selection,
- audio overview, video, slide, and other Studio artifacts,
- artifact download,
- public or invite sharing,
- Google Drive source sync,
- NotebookLM MCP configuration and troubleshooting.
MCP Configuration
Only configure MCP when the target AI client explicitly needs an MCP server. For universal stack work, prefer direct CLI calls or skill-router routing.
Generate a generic MCP config when needed:
nlm setup add json
Use upstream client-specific setup only after checking existing client config to avoid duplicate MCP entries:
nlm setup list
nlm setup add claude-code
nlm setup add gemini
nlm setup add cursor
If a client already has the compact universal skill-router adapter, do not install a full duplicate NotebookLM skill tree into that client. Keep the MCP server as an optional stdio command:
notebooklm-mcp
Quality Gates
Before reporting this integration healthy, verify:
nlm --version
notebooklm-mcp --help
nlm doctor
skill-router skill notebooklm-mcp-cli
skill-router preflight --json "query my NotebookLM notebook about this research"
skill-router skills validate-manifest
nlm doctor may report that Google login is missing. That is an auth state, not a failed installation, unless the user expected the account to be logged in already.
