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Factifai MCP Server

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An MCP server for Factifai, enabling integration with any MCP-compatible AI tool to create and retrieve test results asynchronously.

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Factifai MCP Server

Install in VS Code (npx) Install in VS Code Insiders (npx) Install in Cursor (npx)

Hai Build Amazon Q VS Code Cursor Windsurf Zed

A Model Context Protocol (MCP) server for Factifai integration with any MCP-compatible AI tool. This server is designed to be tool-agnostic, meaning it can be used with any tool that supports the MCP protocol. This server currently exposes tools to create tests asynchronously and get the result of the test.

Table of Contents

See the setup instructions for each

Install in Hai Build

Add the following to your hai_mcp_settings.json file. To open this file from Hai Build, click the "MCP Servers" icon, select the "Installed" tab, and then click "Configure MCP Servers".

See the Hai Build MCP documentation for more info.

{
	"mcpServers": {
		"factifai": {
			"command": "npx",
			"args": ["-y", "@presidio-dev/factifai-mcp-server@latest"],
			"env": {
				"MODEL_PROVIDER": "bedrock|openai",
				"OPENAI_API_KEY": "<your-openai-api-key>",
				"AWS_ACCESS_KEY_ID": "<your-aws-access-key-id>",
				"AWS_SECRET_ACCESS_KEY": "<your-aws-secret-access-key>",
				"AWS_DEFAULT_REGION": "<your-aws-region>"
			}
		}
	}
}
Install in Amazon Q Developer

Add the following to your Amazon Q Developer configuration file. See MCP configuration for Q Developer in the IDE for more details.

The configuration file can be stored globally at ~/.aws/amazonq/mcp.json to be available across all your projects, or locally within your project at .amazonq/mcp.json.

{
	"mcpServers": {
		"factifai": {
			"command": "npx",
			"args": ["-y", "@presidio-dev/factifai-mcp-server@latest"],
			"env": {
				"MODEL_PROVIDER": "bedrock|openai",
				"OPENAI_API_KEY": "<your-openai-api-key>",
				"AWS_ACCESS_KEY_ID": "<your-aws-access-key-id>",
				"AWS_SECRET_ACCESS_KEY": "<your-aws-secret-access-key>",
				"AWS_DEFAULT_REGION": "<your-aws-region>"
			}
		}
	}
}
Install in VS Code (Copilot)

Install in VS Code (npx) Install in VS Code Insiders (npx)

First, enable MCP support in VS Code by opening Settings (Ctrl+,), searching for mcp.enabled, and checking the box.

Then, add the following configuration to your user or workspace settings.json file. See the VS Code MCP documentation for more info.

"mcp": {
  "servers": {
    "factifai": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "@presidio-dev/factifai-mcp-server@latest"],
      "env": {
        "MODEL_PROVIDER": "bedrock|openai",
        "OPENAI_API_KEY": "<your-openai-api-key>",
        "AWS_ACCESS_KEY_ID": "<your-aws-access-key-id>",
        "AWS_SECRET_ACCESS_KEY": "<your-aws-secret-access-key>",
        "AWS_DEFAULT_REGION": "<your-aws-region>"
      }
    }
  }
}
Install in Cursor

The easiest way to install is with the one-click installation button below.

Install in Cursor (npx)

Alternatively, you can manually configure the server by adding the following to your mcp.json file. This file can be located globally at ~/.cursor/mcp.json or within a specific project at .cursor/mcp.json. See the Cursor MCP documentation for more information.

{
	"mcpServers": {
		"factifai": {
			"command": "npx",
			"args": ["--yes", "@presidio-dev/factifai-mcp-server@latest"],
			"env": {
				"MODEL_PROVIDER": "bedrock|openai",
				"OPENAI_API_KEY": "<your-openai-api-key>",
				"AWS_ACCESS_KEY_ID": "<your-aws-access-key-id>",
				"AWS_SECRET_ACCESS_KEY": "<your-aws-secret-access-key>",
				"AWS_DEFAULT_REGION": "<your-aws-region>"
			}
		}
	}
}
Install in Windsurf

Add the following to your ~/.codeium/windsurf/mcp_config.json file. See the Windsurf MCP documentation for more information.

{
	"mcpServers": {
		"factifai": {
			"command": "npx",
			"args": ["-y", "@presidio-dev/factifai-mcp-server@latest"],
			"env": {
				"MODEL_PROVIDER": "bedrock|openai",
				"OPENAI_API_KEY": "<your-openai-api-key>",
				"AWS_ACCESS_KEY_ID": "<your-aws-access-key-id>",
				"AWS_SECRET_ACCESS_KEY": "<your-aws-secret-access-key>",
				"AWS_DEFAULT_REGION": "<your-aws-region>"
			}
		}
	}
}
Install in Zed

You can add the Factifai MCP server in Zed by editing your settings.json file (accessible via the zed: settings action) or by using the Agent Panel's configuration UI (agent: open configuration). See the Zed MCP documentation for more information.

Add the following to your settings.json:

{
	"context_servers": {
		"factifai": {
			"command": {
				"path": "npx",
				"args": ["-y", "@presidio-dev/factifai-mcp-server@latest"],
				"env": {
					"MODEL_PROVIDER": "bedrock|openai",
					"OPENAI_API_KEY": "<your-openai-api-key>",
					"AWS_ACCESS_KEY_ID": "<your-aws-access-key-id>",
					"AWS_SECRET_ACCESS_KEY": "<your-aws-secret-access-key>",
					"AWS_DEFAULT_REGION": "<your-aws-region>"
				}
			}
		}
	}
}

Available Tools

Tool NameDescription
testWithFactifaiStart a test with Factifai
getFactifaiSessionResultGet test result
listFactifaiSessionsList tests

Security

For information about our security policy and how to report security vulnerabilities, please see our Security Policy.