Portkey MCP Server: Comprehensive Integration for AI Applications

Overview: What is Portkey MCP Server?

Portkey MCP Server connects Claude and other AI applications to Portkey's comprehensive API ecosystem, providing a seamless interface for managing AI configurations, workspaces, analytics, and user access. This server enables developers and AI application integrators to leverage Portkey's powerful features while ensuring smooth and secure interactions.

🔧 Core Features & MCP Capabilities

Portkey MCP Server supports essential functionalities such as user management, workspace administration, analytics generation, and more. These capabilities enable AI applications to interact with Portkey’s comprehensive APIs, providing a robust foundation for managing complex workflows and data processes. Below are some of the core features:

User & Access Management

• User Administration: Manage all users within your organization.
• User Invitations: Invite new users with customized roles and permissions.
• Workspace Access Control: Configure user permissions across different workspaces.
• Role-Based Access Control: Assign admin, manager, or member roles at both organizational and workspace levels.

Analytics & Reporting

• Usage Analytics: Track detailed usage patterns for API requests.
• Cost Analysis: Monitor costs associated with API calls over time periods.
• Request Metrics: View request counts, token usage, and response times.
• Filtered Reports: Generate reports based on specific criteria such as status codes, virtual keys, and timelines.

Workspace Management

• Workspace Overview: List and view information about all workspaces.
• Configuration Management: Access and review workspace configurations.
• Virtual Key Management: Monitor API key usage with limits and rate restrictions.
• Workspace Settings: Review metadata and user associations tied to each workspace.

Configuration & API Settings

• Config Listings: View available configurations within your organization.
• Detailed Config Info: Access cache settings, retry policies, and routing strategies.
• Virtual Key Details: Monitor key status, usage limits, and rate restrictions.
• API Integration: Track endpoints and their associated configurations.

⚙️ MCP Architecture & Protocol Implementation

Portkey MCP Server implements a standardized Model Context Protocol (MCP), ensuring seamless integration with supported AI applications. The server architecture is designed to facilitate real-time data exchange and efficient request handling, making it suitable for both development environments and production deployments.

MCP Protocol Flow Diagram

graph TD
    A[AI Application] -->|MCP Client| B[MCP Protocol]
    B --> C[MCP Server]
    C --> D[Data Source/Tool]
    style A fill:#e1f5fe
    style C fill:#f3e5f5
    style D fill:#e8f5e8

MCP Client Compatibility Matrix

MCP Client	Resources	Tools	Prompts	Status
Claude Desktop	✅	✅	✅	Full Support
Continue	✅	✅	❌	Partial
Cursor	✅	❌	✅	Limited

🚀 Getting Started with Installation

From Source

1. Clone this repository:

   git clone https://github.com/r-huijts/portkey-admin-mcp-server.git
   

2. Install dependencies:

   npm install
   

3. Copy the example environment file:

   cp .env.example .env
   

4. Add your Portkey API key to the .env file:

   PORTKEY_API_KEY=your_portkey_api_key_here
   

5. Update your Claude configuration file with the MCP server details:

   {
     "mcpServers": {
       "portkey-server": {
         "command": "node",
         "args": [
           "/path/to/portkey-admin-mcp-server/build/index.js"
         ],
         "env": {
           "PORTKEY_API_KEY": "your_portkey_api_key_here"
         }
       }
     }
   }
   

   Replace /path/to/portkey-admin-mcp-server with the actual installation path.

After updating the configuration, restart Claude Desktop for the changes to take effect.

Installing via Smithery

To install Portkey MCP Server using Smithery:

npx -y @smithery/cli install @r-huijts/portkey-admin-mcp-server --client claude

💡 Key Use Cases in AI Workflows

1. Usage Analytics: Monitor real-time or historical API usage statistics across different models.
2. Performance Metrics: Generate performance reports for AI deployments, including latency and response times.

Real-World Use Case 1: Analyzing Model Performance

Suppose an AI developer needs to track the performance of multiple language generation models used in a corporate setting. By integrating Portkey MCP Server with Claude Desktop, they can:

• Monitor API Calls: Track number of requests per model.
• Generate Reports: Create detailed reports showing response times and token usage.

Real-World Use Case 2: Managing Workspace Access

An organization might want to control access levels for different teams working on distinct projects. Using Portkey MCP Server, this can be achieved by:

• Creating Workspaces: Define individual workspaces for each project.
• Assigning Roles: Set role-based permissions for team members within these workspaces.

🔌 Integration with MCP Clients

Portkey MCP Server is compatible with the following MCP clients:

• Claude Desktop: Full support for AI application integration.
• Continue: Partial support with certain functionalities available.
• Cursor: Limited support focusing on specific tools.

📊 Performance & Compatibility Matrix

Feature	Portkey Admin MCP Server
User Management	✅
Workspace Management	✅
Analytics	✅
Tool Integration	✅

🛠️ Advanced Configuration & Security

Environment Variables

PORTKEY_API_KEY=your_api_key_here

This configuration ensures that your API keys are securely managed and utilized.

MCP Configuration Sample Code

{
  "mcpServers": {
    "portkey-admin-mcp-server": {
      "command": "node",
      "args": [
        "/path/to/server/installation/index.js"
      ],
      "env": {
        "PORTKEY_API_KEY": "your_portkey_api_key_here"
      }
    }
  }
}

❓ Frequently Asked Questions (FAQ)

Q1: How does Portkey MCP Server enhance AI applications?

Portkey MCP Server improves AI application integration by standardizing interactions with various data sources and tools, ensuring compatibility across different environments.

Q2: Can I use this server with other applications besides Claude Desktop?

Yes, except for some limitations, the server is compatible with Continue and Cursor. Integration depends on specific features available in each client.

Q3: How do I secure access to my workspaces?

You can manage roles and permissions within your organization to control who has access to which workspaces through Portkey MCP Server's user management functionality.

Q4: What kind of analytics can I generate using this server?

Analytics include detailed usage statistics, cost analysis, request metrics, and filtered reports based on custom criteria like status codes and virtual keys.

Q5: How do I troubleshoot connection issues with APIs?

Check the setup logs for errors related to API keys or server configurations. Ensure that all environment variables are correctly set and that the server path is correct.

👨‍💻 Development & Contribution Guidelines

Contributions to this project are welcome! Developers interested in contributing can follow these guidelines:

1. Fork the repository.
2. Create a new branch for development.
3. Update the codebase or documentation as needed.
4. Submit a pull request detailing your changes and updates.

🌐 MCP Ecosystem & Resources

For more information on Model Context Protocol (MCP) and its ecosystem, visit the official MCP website. Explore additional resources for developers interested in building custom integrations or contributing to the open-source community.

By leveraging Portkey MCP Server, AI application developers can streamline their workflows, enhance security, and deliver more robust solutions.