Four Ways to Connect Any AI Model to Your Obsidian Knowledge Base

Introduction: Breaking Free from Claude Code's Limitations

In the previous article, we covered how to build an AI-powered knowledge base using Claude Code with Obsidian and the Claudian plugin. However, many readers asked: What if I don't have a Claude Code subscription? What if I only have API access to other models, or I'm using tools like Codex or Cursor — can those be connected to Obsidian too?

The answer is absolutely yes. This article systematically walks through four methods that cover virtually all mainstream AI models and tools, giving your Obsidian knowledge base true "model freedom."

Why Obsidian Is the Ideal Platform for AI Integration

The fundamental reason Obsidian works so well as an AI integration platform lies in its "local-first" design philosophy. Unlike cloud-based note-taking tools such as Notion or Yuque, all of Obsidian's data is stored as plain-text Markdown files on your local file system — no proprietary databases, no encrypted formats, no cloud lock-in. This means any program that can read and write files — whether it's a command-line tool, an IDE, or an API script — can directly manipulate your knowledge base content. An Obsidian Vault is essentially just a folder, where .md files form a knowledge network through bidirectional links ([[]] syntax), and the plugin system provides nearly unlimited extensibility through a Node.js runtime. It's precisely this open underlying architecture that makes the four AI integration methods below possible.

CC Switch: One-Click Integration via Compatible APIs with Claude Code

Core Concept

Many large language models today are compatible with the OpenAI/Claude API format, so the most straightforward approach is to use CC Switch to configure other models' APIs within Claude Code, then leverage the Claudian plugin to build your knowledge base.

Here it's important to understand a key industry context: there's a de facto standard in the AI space — OpenAI's Chat Completions API format. Since OpenAI was the first to define the message structure with system/user/assistant roles and the streaming response protocol, most subsequent model providers (including DeepSeek, Zhipu GLM, MiniMax, Kimi, etc.) have chosen to be compatible with this format. This means that as long as a tool supports configuring a custom API endpoint and key, it can theoretically connect to any OpenAI-compatible model. CC Switch leverages exactly this by modifying Claude Code's API target to forward requests to other compatible services.

Step-by-Step Instructions

1. Install CC Switch: Search for "CC Switch" on GitHub and find the Release page for the project. macOS users download the DMG file; Windows users download the MSI installer.
2. Add a Provider: After installation, open CC Switch and click the "Add" button. You'll see options for multiple providers including DeepSeek, Zhipu, Kimi, Volcengine, and more.
3. Configure the API Key: Taking Volcengine's Ark Coding Plan as an example, a single API can give you access to GLM 5.1, MiniMax, Kimi, DeepSeek, and other models. Create an API Key in the Volcengine Ark console, then paste it into the "Doubao/Seed" configuration field in CC Switch.
4. Switch Models: In CC Switch, you can freely switch between different models — for example, changing the default Doubao model to GLM 5.1.
5. Install the Claudian Plugin: Once configured, specify your Obsidian Vault path in Claude Code and let it automatically install the Claudian plugin. Now you can use any compatible model to manage your knowledge base within Obsidian.

Volcengine Ark Platform: One API Key to Rule Them All

The Volcengine Ark platform deserves a closer look. Volcengine is ByteDance's cloud services platform, and its "Ark" large model service platform offers a unique model aggregation capability: users can call models from multiple providers through a single API endpoint, including Doubao (ByteDance's in-house model), DeepSeek, Zhipu GLM, MiniMax, Moonshot (Kimi), and more. The Ark Coding Plan is a developer-focused package for coding scenarios, typically offering generous free tiers and discounted pricing. This "one API Key to rule them all" approach dramatically reduces the management overhead of switching between multiple models — users don't need to register and top up accounts on each individual platform.

Best Use Cases

This method is ideal for users in China, especially those who have aggregated multiple model APIs through platforms like Volcengine. One-time setup, multiple models available — excellent value for money.

Copilot Plugin: The Best Choice for Official Subscription Users

Step-by-Step Instructions

1. In Obsidian, click "Settings" on the left → "Community Plugins," search for Copilot, and install it.
2. After enabling the plugin, go to its options settings where you'll see configuration entries for Gemini, OpenAI, DeepSeek, and other models.
3. Using DeepSeek as an example: enter your API Key in the corresponding field, click "Add Model," select the model, and change it to "DeepSeek Chat."
4. Click "Copilot Chat" on the left sidebar to start chatting.

Important Notes

The prerequisite for this method is that you have an official subscription or API for the corresponding model. For overseas models (Gemini, OpenAI, Grok, etc.), you need an official account; among Chinese models, DeepSeek is currently the main one directly supported.

If you're already a paying Gemini or OpenAI user, this is the most clean and intuitive approach — no additional tools required.

Terminal Integration: Embedding Command-Line Tools Directly in Obsidian

Compatible Tools

If you're using command-line AI tools like Codex, Gemini CLI, or Qwen Code and don't have a corresponding API, you can integrate them by embedding a terminal within Obsidian.

The Rise of Command-Line AI Tool Ecosystem

In 2025, command-line AI coding tools experienced an explosion in popularity. Beyond Anthropic's Claude Code, OpenAI launched Codex CLI (a terminal coding assistant based on the codex-mini model), Google released Gemini CLI (which calls Gemini 2.5 Pro directly from the terminal), and Alibaba introduced Qwen Code. These tools share common characteristics: they run directly in the terminal, can read and modify local files, support referencing context files via the @ symbol, and typically offer higher operational efficiency than web interfaces. They essentially bring large model capabilities down into the command-line environment that developers know best. Understanding this background makes it clear why embedding a terminal in Obsidian is a natural and efficient integration approach.

Step-by-Step Instructions

1. Go to Obsidian Settings → Community Plugins, search for Terminal, and install it.
2. After installation, an "Open Terminal" option will appear on the left sidebar. Select the "integrated" terminal.
3. If you prefer a side-by-side layout, drag the terminal window to the right side to create an IDE-like split-screen effect.
4. In the terminal, simply type gemini, codex, or any other command-line tool to get started.

Limitations

This approach has one minor drawback: it cannot automatically detect the currently selected note. You need to manually use the @ symbol to specify the file you want to work with — for example, typing @door_agent to include a specific note as context.

That said, since all files in Obsidian are independent Markdown files, this method is essentially equivalent to running AI command-line tools directly within your knowledge base folder — there's no loss of functionality. You can have the AI summarize articles, generate outlines, or even create new notes directly.

Operating on the Knowledge Base Folder Directly from the Command Line

The Simplest Yet Most Universal Approach

Since an Obsidian knowledge base is essentially just a folder containing Markdown files, the simplest method is:

1. Open a terminal and cd to the path of your Obsidian vault.
2. Launch Codex, Gemini CLI, Claude Code, or any other command-line AI tool.
3. Use @ to reference files in the knowledge base for reading, summarizing, editing, and more.

This approach also works with Cursor and VS Code — simply drag your knowledge base folder into the editor and leverage its built-in AI features to manage your notes.

The AI Integration Logic of Cursor and VS Code

Cursor is an AI-native code editor deeply customized on top of VS Code, with built-in features like code completion, conversational editing, and multi-file refactoring. Since an Obsidian knowledge base is just a regular folder, opening it as a project in Cursor or VS Code allows the editor's AI features to work directly on all your Markdown notes. VS Code users can achieve similar capabilities through extensions like GitHub Copilot or Continue. The advantage of this approach is that you can leverage the editor's powerful file management, search, and batch operation features, combined with AI, to perform large-scale knowledge base reorganization and refactoring — such as batch-adding tags to hundreds of notes, generating summaries, or restructuring folder hierarchies.

Practical Demo Results

Using Codex from the command line, you can have it summarize the content of a specific note or generate new articles. For example, entering "Create an outline for me with the title 'How to Add Gemini CLI to Obsidian'" will have Codex output a Markdown-formatted outline directly and generate a corresponding new file in Obsidian's left-side file list.

Comparison of the Four Methods

Method	Core Tool	Best For	Difficulty
CC Switch	Claude Code + Compatible APIs	Users with multiple Chinese models	⭐⭐
Copilot Plugin	Obsidian native plugin	Users with official overseas model subscriptions	⭐
Terminal Integration	Embedded CLI tools	Codex/Gemini CLI users	⭐⭐
Direct Command Line	Folder-level operations	All users (including Cursor/VS Code)	⭐

In theory, these four methods cover virtually every scenario for connecting AI models to Obsidian. No matter what model resources you have at hand, you can find a viable path to inject AI capabilities into your local knowledge base management workflow.

Key Recommendations: If you primarily use Chinese models, prioritize CC Switch + Volcengine. If you're a Gemini/OpenAI subscriber, the Copilot plugin is the most hassle-free option. If you're a command-line enthusiast, Terminal integration and direct command-line operations offer the greatest flexibility.