Integrations
Supports integration with Cursor code editor, allowing users to access and interact with Quickchat AI Agents within the coding environment
Hosts the Quickchat AI MCP repository for access to source code and documentation
The Quickchat AI MCP is available as a package on PyPI for easy installation and integration
Quickchat AI MCP server
The Quickchat AI MCP (Model Context Protocol) server allows you to let anyone plug in your Quickchat AI Agent into their favourite AI app such as Claude Desktop, Cursor, VS Code, Windsurf and more.
Quickstart
- Create a Quickchat AI account and start a 7-day trial of any plan.
- Set up your AI's Knowledge Base, capabilities and settings.
- Go to the MCP page to activate your MCP. Give it Name, Description and (optional) Command. They are important - AI apps need to understand when to contact your AI, what its capabilities and knowledge are.
- That's it! Now you're ready to test your Quickchat AI via any AI app and show it to the world!
Useful links
- Quickstart video youtube.com/watch?v=JE3dNiyZO8w
- Quickstart blog post: quickchat.ai/post/how-to-launch-your-quickchat-ai-mcp
- MCP (Model Context Protocol) explained: quickchat.ai/post/mcp-explained
- The Quickchat AI MCP package on PyPI: pypi.org/project/quickchat-ai-mcp
- The Quickchat AI MCP GitHub repo: github.com/quickchatai/quickchat-ai-mcp
Prerequisite
Install uv
using:
or read more here.
Test with Claude Desktop
Configuration
Go to Settings > Developer > Edit
Config. Open the claude_desktop_config.json file in a text editor. If you're just starting out, the file is going to look like this:
This is where you can define all the MCPs your Claude Desktop has access to. Here is how you add your Quickchat AI MCP:
Go to the Quickchat AI app > MCP > Integration
to find the above snippet with the values of MCP Name, SCENARIO_ID and API_KEY filled out.
Test with Cursor
Configuration
Go to Settings > Cursor Settings > MCP > Add new global MCP server
and include the Quickchat AI MCP snippet:
As before, you can find values for MCP Name, SCENARIO_ID and API_KEY at Quickchat AI app > MCP > Integration
.
Test with other AI apps
Other AI apps will most likely require the same configuration but the actual steps to include it in the App itself will be different. We will be expanding this README as we go along.
Launch your Quickchat AI MCP to the world!
Once you're ready to let other users connect your Quickchat AI MCP to their AI apps, share configuration snippet with them! However, you need to make sure they can use your Quickchat AI MCP without your Quickchat API key. Here is how to do that:
- On the Quickchat App MCP page, turn the Require API key toggle OFF.
- Share the configuration snippet without the API key:
Cool features
- You can control all aspects of your MCP from the Quickchat AI dashboard. One click and your change is deployed. That includes the MCP name and description - all your users need to do is refresh their MCP connection.
- View all conversations in the Quickchat Inbox. Remember: those won't be the exact messages your users send to their AI app but rather the transcript of the AI <> AI interaction between their AI app and your Quickchat AI. 🤯
- Unlike most MCP implementations, this isn't a static tool handed to an AI. It's an open-ended way to send messages to Quickchat AI Agents you create. 🙌
Running from source
Debugging with the MCP inspector
Debugging with Claude Desktop, Cursor or other AI apps
Use the following JSON configuration:
Testing
Make sure your code is properly formatted and all tests are passing:
GitHub Star History
This server cannot be installed
Allows users to integrate their custom Quickchat AI Agents into various AI applications (Claude Desktop, Cursor, VS Code, etc.) through the Model Context Protocol, enabling AI-to-AI interactions.
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