How to Use the ChatBot.com MCP in Cursor

Pull real ChatBot.com interaction logs into Cursor while you write webhook handlers.

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Connect ChatBot.com MCP to Cursor

Create your Vinkius account to connect ChatBot.com to Cursor and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup ChatBot.com with Cursor

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Write better webhooks in Cursor

Trigger `list_chatbot_webhooks` to see exactly what ChatBot.com is actually sending when you write a new endpoint in your editor. Mocking webhook payloads wastes time, so having real chatbot data prevents structural mistakes. The AI grabs the active webhooks and writes your parsing logic based on live routing data. You get working code that handles the exact JSON structure your bot outputs.

Map NLP entities to your database

Run `list_chatbot_entities` right next to your schema file to prevent typos and broken database inserts. Hardcoding variable names causes bugs, so pulling the exact NLP entities fixes that. Cursor reads the custom entities your bot uses for NLP matching and automatically generates the corresponding TypeScript interfaces. The types match your actual bot configuration perfectly.

Replicate user state for local testing

Pull a specific session via `get_chatbot_user_details` so you know exactly what a user clicked before trying to debug a broken flow. This MCP Server grabs the real chat history instead of forcing you to guess the conversation state. You follow up with `list_story_interactions` to see the exact path that user took. Cursor takes that real interaction history and writes a unit test that replicates the bug perfectly.

Setup guide

Set up ChatBot.com MCP in Cursor

Prerequisites

Cursor installed (macOS, Windows, or Linux)
Active Vinkius subscription with a valid endpoint token

1

Open MCP Settings

Go to Cursor Settings → MCP or open the Command Palette (Cmd+Shift+P / Ctrl+Shift+P) and search for "MCP: Add Server".
2

Add the ChatBot.com MCP

Cursor will create or open .cursor/mcp.json in your project root. Paste the JSON snippet on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Enable Agent mode

Open Composer (Cmd+I / Ctrl+I) and switch to Agent mode using the dropdown at the top. MCP tools are only available in Agent mode.
4

Verify the connection

Ask Cursor something like "List my recent ChatBot.com transactions." If the MCP tools are loaded correctly, Cursor will call the ChatBot.com tools automatically. You can also check Settings → MCP for a green status indicator.

.cursor/mcp.json

{
  "mcpServers": {
    "chatbotcom-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by ChatBot. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect ChatBot.com now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about ChatBot.com MCP in Cursor

Create an mcp.json file in your project root directory. Add the Vinkius remote URL under the servers array, then toggle Agent mode on in your chat panel.

The editor cannot push new workflows back to the API. It reads your existing structure to help you write the backend code that supports those conversations.

The agent calls the training data endpoint to fetch unrecognized user phrases. It then uses those real failures to help you write better regex or intent-matching logic in your codebase.

Yes. Committing the configuration file to your repository ensures everyone has access to the same live bot webhooks and entities while coding.

Vinkius manages the authentication layer externally. This MCP setup means your editor only receives a single endpoint token, keeping your actual API credentials off your local machine. The raw conversation transcripts fetched during coding remain strictly in memory.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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