Cursor is a powerful AI-first code editor designed to streamline software development with built-in chat, autocomplete, and AI-powered refactoring tools. By integrating Portkey as the Gateway for your OpenAI API key, you can secure, monitor, and optimize all your LLM traffic—while gaining centralized visibility, caching, cost control, and enterprise-grade governance.

However, Portkey enables robust chat functionality, prompt management, observability, and token-level insights—perfect for teams that want more control over their API usage and compliance while still using Cursor’s interface.

Why Integrate Portkey with Cursor?

Unified AI Gateway - Single interface for 1600+ LLMs with API key management. (not just OpenAI & Anthropic)
CentraliCursor AI observability: Real-time usage tracking for 40+ key metrics and logs for every request
Governance - Real-time spend tracking, set budget limits and RBAC in your Cursor setup
Security Guardrails -a PII detection, content filtering, and compliance controls

If you are an enterprise looking to use Cursor in your organisation, check out this section.

When you use Portkey with Cursor, you won’t have access to some Cursor-specific features that rely on their proprietary models—such as AI autocomplete, “Apply from Chat”, or inline refactoring. These are only available on Cursor’s Pro and Enterprise plans.

1. Setting up Portkey

Portkey allows you to use 1600+ LLMs with your Cursor setup, with minimal configuration required. Let’s set up the core components in Portkey that you’ll need for integration.

Create an Integration

Navigate to the Integrations section on Portkey’s Sidebar. This is where you’ll connect your LLM providers.

Find your preferred provider (e.g., OpenAI, Anthropic, etc.)
Click Connect on the provider card
In the “Create New Integration” window:
- Enter a Name for reference
- Enter a Slug for the integration
- Enter your API Key and other provider specific details for the provider
Click Next Step

In your next step you’ll see workspace provisioning options. You can select the default “Shared Team Workspace” if this is your first time OR chose your current one.

Configure Models

On the model provisioning page:

Leave all models selected (or customize)
Toggle Automatically enable new models if desired

Click Create Integration to complete the integration

Copy the Provider Slug

Once your Integration is creted:

Navigate to the Model Catalog section in your sidebar and Go-to the AI Providers tab.
Find your newly created provider
Copy the slug (e.g., openai-dev-provider-1)

Save this slug - you’ll use it in your Cursor configuration just like how default configs were used before.

Create Default Config

Create a config to use your provider:

Go to Configs in Portkey dashboard

Create new config with:

{
    "virtual_key": "YOUR_PROVIDER_SLUG", //your provider slug from previous step
    "override_params": {
      "model": "gpt-4o" // Your preferred model name exact string
    }
}

Save and note the Config ID for the next step

Configure Portkey API Key

Finally, create a Portkey API key:

Go to API Keys in Portkey
Create new API key
Select your config from Step 5
Generate and save your API key

Save your API key securely - you’ll need it for Cursor integration.

🎉 Voila! that’s all you need to do to setup Portkey. Now let’s see how we can integrate Portkey in our AI application

2. Integrated Portkey with Cursor

You will need your Portkey API key created in Step 1 for this integration

Portkey is an OpenAI compatible API, which means it can be easily integrated with Cursor without any changes to your setup. Here’s how you do it

To access Cursor’s settings and configure it for OpenAI integration, here are the key steps:

Open Settings: Click on “Cursor” in the menu bar and select “Settings…” and choose Cursor Settings.
In the Cursor Settings window, navigate to the Models tab.
Scroll down to find the API Keys section.
Add Your API Keys: Enable the the OpenAI API Key Toggle add you your Portkey API Key.
Toggle on the Override OpenAI Base URL and Enter Portkey’s Base URL: https://api.portkey.ai/v1
Click on Verify.

That’s it! now you have succesfully integrated Cursor with Portkey.

3. Set Up Enterprise Governance for Cursor

Why Enterprise Governance? If you are using Cursor inside your orgnaization, you need to consider several governance aspects:

Cost Management: Controlling and tracking AI spending across teams
Access Control: Managing team access and workspaces
Usage Analytics: Understanding how AI is being used across the organization
Security & Compliance: Maintaining enterprise security standards
Reliability: Ensuring consistent service across all users
Model Management: Managing what models are being used in your setup

Portkey adds a comprehensive governance layer to address these enterprise

Enterprise Implementation Guide

Step 1: Implement Budget Controls & Rate Limits

Step 2: Define Model Access Rules

Step 4: Set Routing Configuration

Portkey allows you to control your routing logic very simply with it’s Configs feature. Portkey Configs provide this control layer with things like:

Data Protection: Implement guardrails for sensitive code and data
Reliability Controls: Add fallbacks, load-balance, retry and smart conditional routing logic
Caching: Implement Simple and Semantic Caching. and more…

Example Configuration:

Here’s a basic configuration to load-balance requests to OpenAI and Anthropic:

{
	"strategy": {
		"mode": "load-balance"
	},
	"targets": [
		{
			"provider":"@YOUR_OPENAI_PROVIDER",
			"override_params": {
				"model": "gpt-model"
			}
		},
		{
			"provider":"@YOUR_ANTHROPIC_PROVIDER",
			"override_params": {
				"model": "claude-sonnet-model"
			}
		}
	]
}

Create your config on the Configs page in your Portkey dashboard. You’ll need the config ID for connecting to Goose’s setup.

Configs can be updated anytime to adjust controls without affecting running applications.

Step 4: Implement Access Controls

Step 3: Implement Access Controls

Create User-specific API keys that automatically:

Track usage per developer/team with the help of metadata
Apply appropriate configs to route requests
Collect relevant metadata to filter logs
Enforce access permissions

Create API keys through:

Example using Python SDK:

from portkey_ai import Portkey

portkey = Portkey(api_key="YOUR_ADMIN_API_KEY")

api_key = portkey.api_keys.create(
    name="frontend-engineering",
    type="organisation",
    workspace_id="YOUR_WORKSPACE_ID",
    defaults={
        "config_id": "your-config-id",
        "metadata": {
            "environment": "development",
            "department": "engineering",
            "team": "frontend"
        }
    },
    scopes=["logs.view", "configs.read"]
)

For detailed key management instructions, see our API Keys documentation.

Step 5: Deploy & Monitor

Enterprise Features Now Available

Cursor now has:

Departmental budget controls
Model access governance
Usage tracking & attribution
Security guardrails
Reliability features

Portkey Features

Now that you have enterprise-grade Cursor setup, let’s explore the comprehensive features Portkey provides to ensure secure, efficient, and cost-effective AI operations.

1. Comprehensive Metrics

Using Portkey you can track 40+ key metrics including cost, token usage, response time, and performance across all your LLM providers in real time. You can also filter these metrics based on custom metadata that you can set in your configs. Learn more about metadata here.

2. Advanced Logs

Portkey’s logging dashboard provides detailed logs for every request made to your LLMs. These logs include:

Complete request and response tracking
Metadata tags for filtering
Cost attribution and much more…

3. Unified Access to 1600+ LLMs

You can easily switch between 1600+ LLMs. Call various LLMs such as Anthropic, Gemini, Mistral, Azure OpenAI, Google Vertex AI, AWS Bedrock, and many more by simply changing the virtual key in your default config object.

4. Advanced Metadata Tracking

Using Portkey, you can add custom metadata to your LLM requests for detailed tracking and analytics. Use metadata tags to filter logs, track usage, and attribute costs across departments and teams.

Custom Metata

5. Enterprise Access Management

Budget Controls

Set and manage spending limits across teams and departments. Control costs with granular budget limits and usage tracking.

Single Sign-On (SSO)

Enterprise-grade SSO integration with support for SAML 2.0, Okta, Azure AD, and custom providers for secure authentication.

Organization Management

Hierarchical organization structure with workspaces, teams, and role-based access control for enterprise-scale deployments.

Access Rules & Audit Logs

Comprehensive access control rules and detailed audit logging for security compliance and usage tracking.

6. Reliability Features

Fallbacks

Automatically switch to backup targets if the primary target fails.

Conditional Routing

Route requests to different targets based on specified conditions.

Load Balancing

Distribute requests across multiple targets based on defined weights.

Caching

Enable caching of responses to improve performance and reduce costs.

Smart Retries

Automatic retry handling with exponential backoff for failed requests

Budget Limits

Set and manage budget limits across teams and departments. Control costs with granular budget limits and usage tracking.

7. Advanced Guardrails

Protect your Project’s data and enhance reliability with real-time checks on LLM inputs and outputs. Leverage guardrails to:

Prevent sensitive data leaks
Enforce compliance with organizational policies
PII detection and masking
Content filtering
Custom security rules
Data compliance checks

Guardrails

Implement real-time protection for your LLM interactions with automatic detection and filtering of sensitive content, PII, and custom security rules. Enable comprehensive data protection while maintaining compliance with organizational policies.

FAQs

How do I update my Provider Budget and Rate limits after creation?

Can I use multiple LLM providers with the same API key?

How do I track costs for different teams?

What happens if a team exceeds their budget limit?

Next Steps

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For enterprise support and custom features, contact our enterprise team.

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On this page

1. Setting up Portkey
2. Integrated Portkey with Cursor
3. Set Up Enterprise Governance for Cursor
Portkey Features
1. Comprehensive Metrics
2. Advanced Logs
3. Unified Access to 1600+ LLMs
4. Advanced Metadata Tracking
5. Enterprise Access Management
6. Reliability Features
7. Advanced Guardrails
FAQs
Next Steps

Ecosystem

LLM Integrations

Cloud Platforms

Guardrails

Plugins

Vector Databases

Agents

AI Apps

Libraries

Tracing Providers

​1. Setting up Portkey

​2. Integrated Portkey with Cursor

​3. Set Up Enterprise Governance for Cursor

​Enterprise Features Now Available

​Portkey Features

​1. Comprehensive Metrics

​2. Advanced Logs

​3. Unified Access to 1600+ LLMs

​4. Advanced Metadata Tracking

Custom Metata

​5. Enterprise Access Management

Budget Controls

Single Sign-On (SSO)

Organization Management

Access Rules & Audit Logs

​6. Reliability Features

Fallbacks

Conditional Routing

Load Balancing

Caching

Smart Retries

Budget Limits

​7. Advanced Guardrails

Guardrails

​FAQs

​Next Steps

1. Setting up Portkey

2. Integrated Portkey with Cursor

3. Set Up Enterprise Governance for Cursor

Enterprise Features Now Available

Portkey Features

1. Comprehensive Metrics

2. Advanced Logs

3. Unified Access to 1600+ LLMs

4. Advanced Metadata Tracking

5. Enterprise Access Management

6. Reliability Features

7. Advanced Guardrails

FAQs

Next Steps