ratanon/claude-code

1# Enterprise deployment overview - Anthropic2 3Source: https://docs.anthropic.com/en/docs/claude-code/third-party-integrations4Last Updated: 2025-06-24T09:05:41.6120575 6---7 8Anthropic home page English Search... Search... Navigation Deployment Enterprise deployment overview Welcome Developer Guide API Guide Claude Code Model Context Protocol (MCP) Resources Release Notes Documentation Developer Discord Support Getting started Overview Set up Quickstart Memory management Common workflows Build with Claude Add Claude Code to your IDE Model Context Protocol (MCP) GitHub Actions Claude Code SDK Troubleshooting Deployment Overview Amazon Bedrock Google Vertex AI Corporate proxy LLM gateway Development containers Administration Identity and Access Management Security Monitoring Costs Reference CLI reference Interactive mode Slash commands Settings Resources Data usage Legal and compliance This page provides an overview of available deployment options and helps you choose the right configuration for your organization.  Provider comparison Feature Anthropic Amazon Bedrock Google Vertex AI Regions Supported countries Multiple AWS regions Multiple GCP regions Prompt caching Enabled by default Enabled by default Contact Google for enablement Authentication API key AWS credentials (IAM) GCP credentials (OAuth/Service Account) Cost tracking Dashboard AWS Cost Explorer GCP Billing Enterprise features Teams, usage monitoring IAM policies, CloudTrail IAM roles, Cloud Audit Logs  Cloud providers Amazon Bedrock Use Claude models through AWS infrastructure with IAM-based authentication and AWS-native monitoring Google Vertex AI Access Claude models via Google Cloud Platform with enterprise-grade security and compliance  Corporate infrastructure Corporate Proxy Configure Claude Code to work with your organizations proxy servers and SSL/TLS requirements LLM Gateway Deploy centralized model access with usage tracking, budgeting, and audit logging  Configuration overview Claude Code supports flexible configuration options that allow you to combine different providers and infrastructure: Understand the difference between: Corporate proxy : An HTTP/HTTPS proxy for routing traffic (set via HTTPS_PROXY or HTTP_PROXY ) LLM Gateway : A service that handles authentication and provides provider-compatible endpoints (set via ANTHROPIC_BASE_URL , ANTHROPIC_BEDROCK_BASE_URL , or ANTHROPIC_VERTEX_BASE_URL ) Both configurations can be used in tandem.  Using Bedrock with corporate proxy Route Bedrock traffic through a corporate HTTP/HTTPS proxy: export CLAUDE_CODE_USE_BEDROCK = 1 export AWS_REGION = us-east-1 export HTTPS_PROXY = 'https://proxy.example.com:8080'  Using Bedrock with LLM Gateway Use a gateway service that provides Bedrock-compatible endpoints: export CLAUDE_CODE_USE_BEDROCK = 1 export ANTHROPIC_BEDROCK_BASE_URL = 'https://your-llm-gateway.com/bedrock' export CLAUDE_CODE_SKIP_BEDROCK_AUTH = 1  Using Vertex AI with corporate proxy Route Vertex AI traffic through a corporate HTTP/HTTPS proxy: export CLAUDE_CODE_USE_VERTEX = 1 export CLOUD_ML_REGION = us-east5 export ANTHROPIC_VERTEX_PROJECT_ID = your-project-id export HTTPS_PROXY = 'https://proxy.example.com:8080'  Using Vertex AI with LLM Gateway Combine Google Vertex AI models with an LLM gateway for centralized management: export CLAUDE_CODE_USE_VERTEX = 1 export ANTHROPIC_VERTEX_BASE_URL = 'https://your-llm-gateway.com/vertex' export CLAUDE_CODE_SKIP_VERTEX_AUTH = 1  Authentication configuration Claude Code uses the ANTHROPIC_AUTH_TOKEN for both Authorization and Proxy-Authorization headers when needed. The SKIP_AUTH flags ( CLAUDE_CODE_SKIP_BEDROCK_AUTH , CLAUDE_CODE_SKIP_VERTEX_AUTH ) are used in LLM gateway scenarios where the gateway handles provider authentication.  Choosing the right deployment configuration Consider these factors when selecting your deployment approach:  Direct provider access Best for organizations that: Want the simplest setup Have existing AWS or GCP infrastructure Need provider-native monitoring and compliance  Corporate proxy Best for organizations that: Have existing corporate proxy requirements Need traffic monitoring and compliance Must route all traffic through specific network paths  LLM Gateway Best for organizations that: Need usage tracking across teams Want to dynamically switch between models Require custom rate limiting or budgets Need centralized authentication management  Debugging When debugging your deployment: Use the claude /status slash command . This command provides observability into any applied authentication, proxy, and URL settings. Set environment variable export ANTHROPIC_LOG=debug to log requests.  Best practices for organizations We strongly recommend investing in documentation so that Claude Code understands your codebase. Many organizations make a CLAUDE.md file (which we also refer to as memory) in the root of the repository that contains the system architecture, how to run tests and other common commands, and best practices for contributing to the codebase. This file is typically checked into source control so that all users can benefit from it. Learn more . If you have a custom development environment, we find that creating a one click way to install Claude Code is key to growing adoption across an organization. Encourage new users to try Claude Code for codebase Q&A, or on smaller bug fixes or feature requests. Ask Claude Code to make a plan. Check Claudes suggestions and give feedback if its off-track. Over time, as users understand this new paradigm better, then theyll be more effective at letting Claude Code run more agentically. Security teams can configure managed permissions for what Claude Code is and is not allowed to do, which cannot be overwritten by local configuration. Learn more . MCP is a great way to give Claude Code more information, such as connecting to ticket management systems or error logs. We recommend that one central team configures MCP servers and checks a .mcp.json configuration into the codebase so that all users benefit. Learn more . At Anthropic, we trust Claude Code to power development across every Anthropic codebase. We hope you enjoy using Claude Code as much as we do!  Next steps Set up Amazon Bedrock for AWS-native deployment Configure Google Vertex AI for GCP deployment Implement Corporate Proxy for network requirements Deploy LLM Gateway for enterprise management Settings for configuration options and environment variables Was this page helpful? Yes No Troubleshooting Amazon Bedrock On this page Provider comparison Cloud providers Corporate infrastructure Configuration overview Using Bedrock with corporate proxy Using Bedrock with LLM Gateway Using Vertex AI with corporate proxy Using Vertex AI with LLM Gateway Authentication configuration Choosing the right deployment configuration Direct provider access Corporate proxy LLM Gateway Debugging Best practices for organizations Next steps9 10---11Document ID: en__docs__claude-code__third-party-integrations