Fixing Anthropic Claude Compatibility In Obsidian

Nov 14, 2025 by Alex Johnson 50 views

Fixing Compatibility Issues with Anthropic Claude in Obsidian AI Tagger

Hey there! Have you been trying to get the Obsidian AI Tagger plugin to play nicely with Anthropic's Claude? If so, you might have run into a few snags, as I did. This article will walk you through the common issues I encountered and how I whipped up a quick proxy to get things working. Let's dive in and make sure your Obsidian notes can leverage the power of Claude seamlessly.

The Problem: Navigating Compatibility Hurdles

When I first tried to connect the Obsidian AI Tagger plugin to Anthropic Claude, I hit a few roadblocks. The plugin, designed with flexibility in mind, wasn't perfectly aligned with Claude's specific API requirements. These are the main issues I faced:

CORS Errors: The dreaded "Cross-Origin Resource Sharing" errors popped up, indicating that the plugin's requests weren't being authorized by the Anthropic API. This is a common issue when your browser or application tries to access resources from a different domain than the one the page originated from.
Legacy/Deprecated Endpoint: The plugin was trying to use an older API endpoint that might not be fully supported by Anthropic. API endpoints evolve, and using an outdated one can lead to failures or unexpected behavior.
OpenAI-Style Message Format Mismatch: The Obsidian plugin and, by extension, the AI Tagger, likely expects a specific format for sending messages, reminiscent of OpenAI's API. However, Claude uses a different structure, leading to parsing errors.

It's worth mentioning that my testing might have been affected by the use of a newer Claude model. Newer models often come with their own API quirks, so staying updated and adapting to these changes is critical to ensuring smooth integration.

In essence, it was a battle of formats and access restrictions – a common struggle in the world of API integrations. Let’s get these fixed.

Crafting a Proxy: The Solution

To overcome these hurdles, I created a simple proxy server using Python and the Flask framework. This proxy acts as an intermediary, taking requests from the Obsidian plugin, reformatting them to suit Anthropic's needs, and then forwarding them to the Claude API. It also handles the response, converting it back to a format that the plugin understands. Essentially, it bridges the gap between the plugin and the API, making them compatible.

Setting Up the Proxy

Here’s a step-by-step guide to get your proxy up and running:

Install Dependencies: First, make sure you have Python installed. Then, install the necessary libraries: Flask and Requests. You can do this with pip, Python’s package installer.
```
pip install flask requests
```

The Code: Below is the code for the proxy. Save this as a Python file (e.g., claude_proxy.py). It’s designed to forward requests to Anthropic's API and transform the request and responses to resolve compatibility problems.

from flask import Flask, request, Response
import requests
import json

app = Flask(__name__)

@app.route('/', defaults={'path': ''}, methods=['GET', 'POST', 'PUT', 'DELETE', 'OPTIONS'])
@app.route('/<path:path>', methods=['GET', 'POST', 'PUT', 'DELETE', 'OPTIONS'])
def proxy(path):
    if request.method == 'OPTIONS':
        response = Response()
        response.headers['Access-Control-Allow-Origin'] = '*'
        response.headers['Access-Control-Allow-Methods'] = 'GET, POST, PUT, DELETE, OPTIONS'
        response.headers['Access-Control-Allow-Headers'] = 'anthropic-dangerous-direct-browser-access, *'
        return response
    
    url = f'https://api.anthropic.com/{path}'
    headers = {k: v for k, v in request.headers if k.lower() != 'host'}
    # Ensure the required header is present
    if 'anthropic-dangerous-direct-browser-access' not in headers:
        headers['anthropic-dangerous-direct-browser-access'] = 'true'
    
    # Transform request body for Messages API
    data = request.get_data()
    if request.method == 'POST' and 'messages' in path:
        try:
            body = json.loads(data)
            if 'messages' in body:
                # Extract system messages and convert to system parameter
                system_messages = [msg['content'] for msg in body['messages'] if msg.get('role') == 'system']
                body['messages'] = [msg for msg in body['messages'] if msg.get('role') != 'system']
                
                if system_messages:
                    body['system'] = '\n\n'.join(system_messages)
                
                data = json.dumps(body).encode('utf-8')
                headers['Content-Length'] = str(len(data))
        except (json.JSONDecodeError, KeyError):
            pass  # If we can't parse or transform, send as-is
    
    resp = requests.request(
        method=request.method,
        url=url,
        headers=headers,
        data=data,
        allow_redirects=False
    )
    
    # Transform response body from Anthropic to OpenAI format
    response_data = resp.content
    if request.method == 'POST' and 'messages' in path and resp.status_code == 200:
        try:
            anthropic_response = json.loads(resp.content)
            if 'content' in anthropic_response and isinstance(anthropic_response['content'], list):
                # Transform Anthropic Messages API response to OpenAI format
                openai_response = {
                    "id": anthropic_response.get('id', ''),
                    "object": "chat.completion",
                    "created": 0,  # Anthropic doesn't provide timestamp
                    "model": anthropic_response.get('model', ''),
                    "choices": [{
                        "index": 0,
                        "message": {
                            "role": "assistant",
                            "content": ''.join([
                                block['text'] for block in anthropic_response['content']
                                if block.get('type') == 'text'
                            ])
                        },
                        "finish_reason": anthropic_response.get('stop_reason', 'stop')
                    }],
                    "usage": anthropic_response.get('usage', {})
                }
                response_data = json.dumps(openai_response).encode('utf-8')
        except (json.JSONDecodeError, KeyError):
            pass  # If we can't parse or transform, send as-is
    
    response = Response(response_data, resp.status_code)
    response.headers['Access-Control-Allow-Origin'] = '*'
    for key, value in resp.headers.items():
        if key.lower() not in ['content-encoding', 'transfer-encoding', 'content-length']:
            response.headers[key] = value
    
    return response

if __name__ == '__main__':
    app.run(port=8080)

Run the Proxy: Open your terminal, navigate to the directory where you saved claude_proxy.py, and run the script.
```
python claude_proxy.py
```
This will start the proxy server, typically on port 8080. You can change the port in the code if needed.

Configuring the Obsidian AI Tagger Plugin

Once the proxy is running, configure the Obsidian AI Tagger plugin to use it. Here’s how:

Cloud Provider: In the plugin settings, select claude as the cloud provider.
API Endpoint: Enter the address of your proxy server. This is where the plugin will send its requests.
- http://localhost:8080/v1/messages (If your proxy is running on port 8080.)
Model Name: Specify the Claude model you want to use. Make sure the model name is one that is supported by Anthropic and you have access to. For example:
- claude-haiku-4-5-20251001

After these settings, the plugin should be able to communicate with Anthropic Claude through your proxy, effectively bypassing the compatibility issues.

Decoding the Proxy Code

Let's break down the code to understand its workings.

Imports: The code begins by importing necessary libraries:
- flask: For creating the web application and handling HTTP requests.
- requests: For making HTTP requests to the Anthropic API.
- json: For encoding and decoding JSON data.
Flask App: A Flask app instance is initialized to handle web requests.
Proxy Route: The @app.route decorator defines the route for the proxy. It captures all requests (GET, POST, PUT, DELETE, OPTIONS) and forwards them to the Anthropic API. The path variable captures the specific API endpoint being requested (e.g., /v1/messages).
CORS Handling: Before anything else, the OPTIONS method is handled to set the necessary Access-Control-Allow-Origin and other CORS headers. This is a crucial step to solve CORS issues.
Headers: The code passes headers from the original request to the Anthropic API, making sure to include the required anthropic-dangerous-direct-browser-access header. It also handles the host header correctly.
Request Transformation: The code transforms the request body, specifically for the /messages endpoint. It extracts system messages (if any) and places them in the appropriate format. This is crucial for Claude’s API to understand the request.
API Request: The requests.request() function sends the request to the Anthropic API. It uses the same method (GET, POST, etc.) and forwards the data and headers.
Response Transformation: The response from Anthropic is then transformed back into a format that the Obsidian plugin can understand (like OpenAI format). This includes mapping the content and handling the 'stop_reason'.
Response: The transformed response is sent back to the Obsidian plugin.
Running the App: The if __name__ == '__main__': block starts the Flask development server on port 8080 when you run the script.

This simple proxy acts as a translator, allowing the plugin and the API to understand each other.

Troubleshooting Tips

Check the Logs: If something isn't working, check the terminal where the proxy is running for error messages. They can provide valuable clues.
Verify the API Key: Make sure your Anthropic API key is correctly configured. The proxy itself doesn't directly handle the API key, but the plugin uses it. Make sure the API key is correct and has the necessary permissions.
Network Issues: Ensure there are no network issues preventing communication between your Obsidian app, the proxy, and the Anthropic API.
Model Compatibility: Double-check that the model name you've entered is correct and that it is accessible in your Anthropic account.
Plugin Updates: Keep your Obsidian AI Tagger plugin updated to the latest version. Developers often release updates to improve compatibility and fix bugs.

In Conclusion: Harmonizing Obsidian and Claude

By creating and using this proxy, you can successfully integrate Anthropic Claude with the Obsidian AI Tagger plugin. This method helps overcome common compatibility problems, such as CORS errors, deprecated endpoints, and message format discrepancies. Remember to configure the proxy in the plugin settings with the correct endpoint and model name. With these steps, you should be able to enjoy the advanced features of Claude within your Obsidian environment. Happy note-taking and AI-assisted writing!

For more information, consider checking out Anthropic's official documentation at this link:

Anthropic API Documentation