NiCE Cognigy MCP Server - Cognigy Documentation

NiCE Cognigy MCP Server

The NiCE Cognigy MCP Server is an npm package that provides a Model Context Protocol (MCP) server for connecting MCP clients like Claude, Cursor, or VS Code to the Cognigy.AI REST API. With the NiCE Cognigy MCP server, you can create, test, and iteratively improve LLM-based AI Agents without leaving your development environment.

Key Benefits

Comprehensive API coverage. Use workflow tools in the NiCE Cognigy MCP Server to cover the Cognigy.AI API for end-to-end automation.
Fast AI Agent setup and iteration. Build an AI Agent persona, Flow, Node, and REST Endpoint in one workflow, then test, refine, and repeat until it performs as expected.
Knowledge and guidance built in. Access Knowledge Stores for RAG use cases to give your AI Agent the information it needs.
Reliable and safe operations. Configure rate limiting, Zod input validation, and standardized RFC 7807 error responses for safe operations with the NiCE Cognigy MCP Server.

Prerequisites

A Cognigy.AI API key. To create one, go to User Menu > My Profile > API Keys > Create New.
A Cognigy.AI API base URL. For example, for the trial environment, use https://api-trial.cognigy.ai.
An MCP-compatible client such as Claude Desktop, Claude Code, Codex, Cursor, or VS Code with GitHub Copilot.
Node.js 20 or later is required for command-line and manual setup.

How to Set Up

Claude Desktop (.mcpb)
- Download the .mcpb file from the npm package page.
- Double-click the file to open the installation dialog in Claude Desktop.
- Enter your Cognigy.AI API base URL and API key.
CLI
- Run the setup command for your MCP client in the CLI. The command prompts you to enter your Cognigy.AI API base URL and API key, then automatically updates the MCP client configuration.
Manual

MCP Client	Command
Claude Desktop	`npx @cognigy/mcp-server init --client claude`
Claude Code	`npx @cognigy/mcp-server init --client claude-code`
Codex	`npx @cognigy/mcp-server init --client codex`
Cursor	`npx @cognigy/mcp-server init --client cursor`
VS Code (Copilot)	`npx @cognigy/mcp-server init --client vscode`

Restart your MCP client after setup completes.

Add the server definition directly to your MCP client configuration file.

Configuration Examples

For Claude Desktop, Claude Code, and Cursor:

{
  "mcpServers": {
    "cognigy": {
      "command": "npx",
      "args": ["-y", "@cognigy/mcp-server"],
      "env": {
        "COGNIGY_API_BASE_URL": "your-api-base-url",
        "COGNIGY_API_KEY": "your-api-key-here"
      }
    }
  }
}

For Codex:

[mcp_servers.cognigy]
command = "npx"
args = ["-y", "@cognigy/mcp-server"]

[mcp_servers.cognigy.env]
COGNIGY_API_BASE_URL = "your-api-base-url"
COGNIGY_API_KEY = "your-api-key"

For VS Code (Copilot):

{
  "servers": {
    "cognigy": {
      "command": "npx",
      "args": ["-y", "@cognigy/mcp-server"],
      "env": {
        "COGNIGY_API_BASE_URL": "your-api-base-url",
        "COGNIGY_API_KEY": "your-api-key"
      }
    }
  }
}

Restart your MCP client to ensure it is connected to the NiCE Cognigy MCP server.

Security

API keys are passed through environment variables and are never logged.
All inputs are validated with Zod schemas before reaching the API.
Rate limiting protects the API from excessive or abusive requests.

Privacy

The NiCE Cognigy MCP Server sends requests only to the Cognigy.AI API base URL. The server doesn’t collect, store, or share any data. All data stays between your MCP client and your Cognigy.AI instance. For more information, see the Cognigy Privacy Policy.

How to Use

Once the server is connected to your MCP client, you can interact with Cognigy.AI using natural language prompts. The following examples show prompts for common workflows and the tools the MCP client runs in response. For a full list of available tools, refer to the Tools section of the NiCE Cognigy MCP Server npm package documentation.

Create an AI Agent

Create a Cognigy AI Agent called "Support Bot" in Project <projectId>.
Give it a helpful customer support persona, set up GPT-4 as the LLM,
and return the endpoint URL so I can test it.

Test the Agent

Talk to my Support Bot at <endpointUrl> and ask "How do I reset my password?"

Improve the Agent

Update the job description to make the response more concise and actionable.
Talk to it again and compare the responses.

Add a Knowledge Store

Create a Knowledge Store in Project <projectId>, add the URL
https://docs.example.com/faq as a source, then attach it to my Support Bot
so the AI Agent can reference it to answer questions.

Review Existing Resources

List all my Cognigy.AI Projects and show which AI Agents exist in each one.

Export and Import Packages

Upload the package at `/absolute/path/to/support-bot.zip` into Project <projectId>,
show me the import preview, then import it using the default selections.

More Information

Last modified on May 26, 2026.