Gemini Notebook (NotebookLM) MCP plugin for DeepSeek Harness

Use Google NotebookLM / Gemini Notebook from the DeepSeek Harness (DSH) agent
53 tools for notebooks, sources, grounded Q&A, web research, audio podcasts, video, slides, quizzes and more.

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dsh-gemini-notebook-mcp is a DeepSeek Harness plugin bundle (a "dsh plugin") that connects the Gemini Notebook / NotebookLM MCP server (notebooklm-mcp-cli) to the DSH agent. Once it's installed, you can ask DSH things like "create a notebook about quantum computing, add these three URLs and generate a podcast" and the agent does it through Gemini Notebook (formerly Google NotebookLM).

It contains configuration only, with no code of its own. It uses DSH's built-in MCP client, @deepseek-ai/dsh-mcp-client, to start the notebooklm-mcp server over stdio. The server's tools then appear in DSH as mcp__gemini-notebook__<tool>.

Contents

• What is DeepSeek Harness?
• Features
• Requirements
• Installation
• Usage examples
• Available tools
• Configuration
• Troubleshooting
• FAQ
• How it works
• Credits and disclaimer

What is DeepSeek Harness?

DeepSeek Harness (DSH) is DeepSeek's AI agent harness. Its motto is "Everything is a Plugin." It runs as a Desktop app, a Web GUI (dsh web), a headless CLI, an ACP server or an SDK. Every capability, including tools, UI panels, models, skills and MCP connections, is a Cordis plugin. Plugins are composed into profiles from bundles: npm-style packages that declare a cordis.patch.yml.

This repository is one of those bundles. It adds Gemini Notebook as an MCP tool provider to your DSH profile.

Features

• 📚 Notebooks: list, create, rename, describe and delete Gemini Notebook notebooks.
• 🔗 Sources: add URLs, YouTube videos, pasted text, Google Drive docs and local files (PDF, DOCX, audio, images and more); read raw source text; sync stale Drive sources.
• 💬 Grounded Q&A: ask questions answered only from your sources, with citations. Queries can also run across several notebooks. Chats stay in the NotebookLM web history.
• 🔎 Research: fast or deep web research and Google Drive search, with import of the sources it finds.
• 🎙️ Studio: generate Audio Overviews (podcasts), video overviews, slide decks, infographics, reports, quizzes, flashcards, mind maps, data tables and interactive reports, then download them.
• 🗂️ Organization: notes, source labels, collections, tags, aliases, batch operations and multi-step pipelines.
• 🤝 Sharing: public links and collaborator invites.
• 👤 Accounts: multiple Google profiles, usage quota checks and NotebookLM Enterprise.

Requirements

Requirement	Notes
DeepSeek Harness	Desktop app or dsh web, with a profile that includes Plugin Manager (the default ones do)
uv	Used to install the Python MCP server
notebooklm-mcp-cli	Provides the nlm CLI and the notebooklm-mcp server
A Google account	With access to Gemini Notebook / NotebookLM

Tested with DeepSeek Harness Desktop 0.2.1 on macOS and notebooklm-mcp-cli 0.15.4.

Installation

1. Install and sign in to the MCP server

uv tool install notebooklm-mcp-cli   # installs nlm + notebooklm-mcp into ~/.local/bin
nlm login                            # opens a browser; sign in to Google once
nlm login --check                    # should print "Authentication valid!"

2. Install the DSH plugin bundle

Option A: ask the DSH agent, in a session where the agent has the plugin_manager tool (for example Creator mode):

Install the DSH bundle from github:EdgarsKalnins/dsh-gemini-notebook-mcp

Option B: Plugins page. Open Plugins in the DSH sidebar, choose install and enter github:EdgarsKalnins/dsh-gemini-notebook-mcp.

Option C: from a local clone, which lets you edit the config before installing:

git clone https://github.com/EdgarsKalnins/dsh-gemini-notebook-mcp.git

Then ask the DSH agent: "Install the bundle at /absolute/path/to/dsh-gemini-notebook-mcp".

With hot reload (the default), the tools appear right away and no restart is needed.

3. Verify

Ask the agent: "Call gemini-notebook server_info and list my notebooks." server_info should report auth_status: configured and 53 visible tools.

Usage examples

Talk to the DSH agent in plain language:

• "List my Gemini Notebook notebooks."
• "Create a notebook called AI Strategy Research and add https://example.com/article as a source."
• "Do deep research on cloud marketplace trends and import the cited sources."
• "What are the key findings in my Product Research notebook? Cite the sources."
• "Generate a deep-dive audio podcast from this notebook and download it when it's ready."
• "Make a 10-question hard quiz and a study guide from my lecture notes notebook."
• "Create a slide deck, then revise slide 3 to be more concise."
• "Which Google Drive sources in this notebook are out of date? Sync them."

Available tools

The tools are exposed as mcp__gemini-notebook__<name>.

Group	Tools
Notebooks	notebook_list, notebook_get, notebook_describe, notebook_create, notebook_rename, notebook_delete
Sources	source_add, source_list_drive, source_describe, source_get_content, source_rename, source_sync_drive, source_delete
Chat & query	notebook_query, notebook_query_start, notebook_query_status, chat_configure, chat_list, chat_get, chat_export, cross_notebook_query
Studio	studio_create, studio_status, studio_revise, studio_delete, report, download_artifact, download_all_artifacts, export_artifact
Research	research_start, research_status, research_import
Notes	note, chat_save_to_note
Organization	label, tag, collection_list, collection_create, collection_edit, collection_set_emoji, collection_delete
Automation	batch, pipeline
Sharing	notebook_share_status, notebook_share_public, notebook_share_invite, notebook_share_batch
Account	profile, alias, refresh_auth, save_auth_tokens, usage_get, server_info

Destructive tools such as notebook_delete, source_delete, studio_delete and sharing do nothing unless confirm=True is passed. Studio generation also asks for confirmation.

Configuration

All settings are in cordis.patch.yml:

- insert:
    - id: gemini-notebook-mcp
      name: '@deepseek-ai/dsh-mcp-client'
      config:
        serverName: gemini-notebook
        transport: stdio
        command: !!js '`${process.env.HOME}/.local/bin/notebooklm-mcp`'
        args: ['--transport', 'stdio']
        env:
          NOTEBOOKLM_HL: en
          NOTEBOOKLM_QUERY_TIMEOUT: '150'
        toolCallTimeoutMs: 180000
        failOnStartupError: true

Common changes:

Goal	Change
Reduce context usage (53 tool schemas go with every request)	Add NOTEBOOKLM_DISABLED_GROUPS: studio,sharing,research under env
Hide or show single tools	NOTEBOOKLM_DISABLED_TOOLS / NOTEBOOKLM_ENABLED_TOOLS
Run without installing (via uvx)	command: uvx, args: ['--from', 'notebooklm-mcp-cli', 'notebooklm-mcp']
Binary in a different location	Set command to the output of which notebooklm-mcp
Download folder for artifacts	NOTEBOOKLM_DOWNLOAD_DIR: /path/to/dir
Language of the interface and generated artifacts	NOTEBOOKLM_HL: de (any BCP-47 tag, for example es-419)
NotebookLM Enterprise	NOTEBOOKLM_BASE_URL, NOTEBOOKLM_PROJECT_ID, NOTEBOOKLM_LOCATION

Tool groups: notebooks_read, notebooks_manage, sources_read, sources_manage, chat, query_multi, organization, automation, notes, auth, server, sharing, research, studio.

DSH scrubs secret-looking variables (*TOKEN*, *KEY*, …) from the server's environment. The Google login lives in ~/.notebooklm-mcp-cli, and is encrypted there if you use nlm auth storage set protected.

Troubleshooting

Symptom	Fix
Plugin fails to activate	Check that ~/.local/bin/notebooklm-mcp --help works, or fix command
auth_status: stale or auth errors	Run nlm login, then call refresh_auth or reload the plugin
Queries time out on large notebooks	Raise NOTEBOOKLM_QUERY_TIMEOUT and toolCallTimeoutMs, or use notebook_query_start + notebook_query_status
Rate-limit / quota errors	Ask the agent to call usage_get; NotebookLM meters a rolling ~5 h window plus a weekly cap
Old server version	uv tool upgrade notebooklm-mcp-cli, then reload the plugin

FAQ

How do I use NotebookLM in DeepSeek Harness? Install notebooklm-mcp-cli, run nlm login, then install this bundle in DSH. The agent gets the full set of Gemini Notebook tools.

Is this an official Google or DeepSeek project? No. It's a community DSH plugin. The MCP server comes from jacob-bd/gemini-notebook-mcp-cli and uses undocumented NotebookLM APIs.

Does it work with Claude Code, Cursor or Codex? This bundle is for DeepSeek Harness only. For other agents, use upstream's nlm setup wizard.

Can I generate a NotebookLM podcast (Audio Overview) from DSH? Yes. Ask the agent to create an audio artifact. It polls studio_status and downloads the result with download_artifact.

Does it support multiple Google accounts? Yes. Run nlm login --profile work, then have the agent call profile(action="switch", name="work").

How it works

DeepSeek Harness agent
   └─ @deepseek-ai/dsh-mcp-client  (row "gemini-notebook-mcp", from this bundle's cordis.patch.yml)
        └─ stdio ─► notebooklm-mcp  (Python, notebooklm-mcp-cli)
                      └─ HTTPS ─► Gemini Notebook / NotebookLM (your Google session)

Repository layout:

File	Purpose
package.json	Bundle manifest (dsh.bundle.patch)
cordis.patch.yml	Inserts the MCP client row
locale/*.json	Title and description shown in DSH Plugin Manager
icon.svg	Plugin icon

Credits and disclaimer

• MCP server and CLI: jacob-bd/gemini-notebook-mcp-cli (MIT).
• Agent harness: deepseek-ai/deepseek-harness.
• More DSH plugins: awesome-dsh-plugin · GitHub topic dsh-plugin.

NotebookLM and Gemini are trademarks of Google LLC. This project is not affiliated with Google or DeepSeek. The upstream server uses undocumented APIs that may change, and use may not match Google's Terms of Service. Use it at your own risk.

License

MIT