AI Coding Assistants Integration¶

Connect your favorite AI coding assistants to AWS Bedrock models through stdapi.ai. Get intelligent code completions, chat assistance, and codebase understanding with powerful AWS models like Claude, Kimi K2 thinking, and Qwen Coder Next—no vendor lock-in required.

About AI Coding Assistants¶

AI coding assistants are IDE extensions and terminal tools that leverage large language models to enhance developer productivity. These tools provide real-time code completions, intelligent suggestions, natural language code generation, and interactive chat capabilities directly within your coding environment—acting as AI pair programmers that understand your codebase context.

What AI coding assistants can do:

• Real-time completions - Autocomplete code as you type with context awareness
• Interactive chat - Ask questions about your codebase, get explanations
• Code generation - Natural language to code conversion
• Refactoring - Intelligent code improvements and optimization suggestions
• Documentation - Auto-generate comments, docstrings, and READMEs
• Testing - Create unit tests, debug issues, suggest fixes
• Git integration - Generate commit messages, review diffs
• Multi-language - Support for Python, JavaScript, TypeScript, Go, Rust, Java, and more

Why AI Coding Assistants + stdapi.ai?¶

%%{init: {'flowchart': {'htmlLabels': true}} }%%
flowchart LR
  ide["<img src='../styles/logo_vscode.svg' style='height:64px;width:auto;vertical-align:middle;' /> IDE + AI Assistant"] --> stdapi["<img src='../styles/logo.svg' style='height:64px;width:auto;vertical-align:middle;' /> stdapi.ai"]
  stdapi --> bedrock["<img src='../styles/logo_amazon_bedrock.svg' style='height:64px;width:auto;vertical-align:middle;' /> AWS Bedrock"]

Prerequisites¶

OpenAI-Compatible Coding Assistants¶

Popular Tools: Cline | JetBrains AI Assistant | Continue.dev | Cursor | Windsurf

Most IDE coding assistants use the OpenAI-compatible API. Configure them by pointing to stdapi.ai's /v1 endpoint.

Configuration¶

Most AI coding assistants follow a similar configuration pattern. The exact menu location and field names may vary, but the core settings remain consistent.

Chat Completions¶

All coding assistants use chat completions for interactive conversations, code generation, and explanations.

Tool Calling Support¶

stdapi.ai fully supports tool calling (function calling) through the chat completions API, which is essential for autonomous and efficient coding agents.

Code Completions¶

Some coding assistants support dedicated code completion endpoints for real-time suggestions as you type.

Anthropic-Compatible Coding Assistants¶

Popular Tools: Claude Code | Aider | JetBrains AI Assistant (With Claude code ACP)

Tools that use the Anthropic messages API natively can be connected to stdapi.ai's /anthropic endpoint, enabling them to use Claude models via AWS Bedrock.

Claude Code¶

Claude Code is Anthropic's agentic coding tool that runs in the terminal.

Configuration¶

Create or edit ~/.claude/claude.json:

{
  "env": {
    "ANTHROPIC_AUTH_TOKEN": "YOUR_API_KEY",
    "ANTHROPIC_BASE_URL": "https://YOUR_STDAPI_URL/anthropic",
    "ANTHROPIC_DEFAULT_OPUS_MODEL": "anthropic.claude-opus-4-6-v1",
    "ANTHROPIC_DEFAULT_SONNET_MODEL": "anthropic.claude-sonnet-4-6",
    "ANTHROPIC_DEFAULT_HAIKU_MODEL": "anthropic.claude-haiku-4-5-20251001-v1:0"
  }
}

• Replace YOUR_STDAPI_URL with your stdapi.ai deployment URL (e.g., https://api.example.com or http://localhost:8000 for local)
• Replace YOUR_API_KEY with your stdapi.ai API key
• The /anthropic path prefix is configured via the ANTHROPIC_ROUTES_PREFIX setting (default: /anthropic)
• The ANTHROPIC_DEFAULT_*_MODEL variables pin each model tier to a specific Bedrock model ID — recommended for production stability. Without them, Claude Code resolves aliases (opus, sonnet, haiku) which may change when Anthropic releases new versions. stdapi.ai also accepts the short alias names (e.g. claude-sonnet-4-6) as a convenience.

Effort-Based Reasoning¶

Claude Code supports effort levels that control how much reasoning the model applies — lower effort is faster and cheaper; higher effort provides deeper thinking for complex tasks.

Supported models via stdapi.ai:

Setting effort level:

# Per session at launch
claude --model sonnet --effort high

# Persist across sessions (env var takes precedence over all other settings)
export CLAUDE_CODE_EFFORT_LEVEL=high

# Or add to claude.json

{
  "effortLevel": "medium"
}

During a session, use /effort low, /effort medium, /effort high, or /effort max to change levels on the fly.

Declaring Model Capabilities¶

When you pin a non-Claude Bedrock model ID, Claude Code may not recognize it and will silently disable effort and thinking features. Use ANTHROPIC_DEFAULT_*_MODEL_SUPPORTED_CAPABILITIES to declare what the model actually supports:

Example — Nova 2 with effort enabled:

{
  "env": {
    "ANTHROPIC_AUTH_TOKEN": "YOUR_API_KEY",
    "ANTHROPIC_BASE_URL": "https://YOUR_STDAPI_URL/anthropic",
    "ANTHROPIC_DEFAULT_SONNET_MODEL": "amazon.nova-2-lite-v1:0",
    "ANTHROPIC_DEFAULT_SONNET_MODEL_NAME": "Nova 2 Lite",
    "ANTHROPIC_DEFAULT_SONNET_MODEL_SUPPORTED_CAPABILITIES": "effort",
    "DISABLE_PROMPT_CACHING": "1"
  }
}

Example — Claude with full capabilities declared (e.g. for a Bedrock ARN or inference profile):

{
  "env": {
    "ANTHROPIC_DEFAULT_OPUS_MODEL": "arn:aws:bedrock:us-east-1:123456789012:application-inference-profile/my-opus",
    "ANTHROPIC_DEFAULT_OPUS_MODEL_NAME": "Opus via Bedrock",
    "ANTHROPIC_DEFAULT_OPUS_MODEL_SUPPORTED_CAPABILITIES": "effort,max_effort,thinking,adaptive_thinking,interleaved_thinking"
  }
}

Using Non-Claude Models¶

Claude Code is optimized for Claude models and enables reasoning by default. When routing non-Claude models through stdapi.ai, this can cause API errors if the model does not support reasoning parameters. Configure based on the model's capabilities:

Models with effort support (Nova 2, DeepSeek V3) — declare effort capability:

{
  "env": {
    "ANTHROPIC_DEFAULT_SONNET_MODEL": "amazon.nova-2-lite-v1:0",
    "ANTHROPIC_DEFAULT_SONNET_MODEL_SUPPORTED_CAPABILITIES": "effort",
    "DISABLE_PROMPT_CACHING": "1"
  }
}

Models without reasoning support (Qwen, Kimi K2, Mistral, etc.) — disable all Claude-specific features:

{
  "env": {
    "ANTHROPIC_DEFAULT_SONNET_MODEL": "moonshot.kimi-k2-instruct",
    "DISABLE_PROMPT_CACHING": "1",
    "MAX_THINKING_TOKENS": "0"
  }
}

Common configuration issues with non-Claude models:

• Prompt caching — Claude Code sends cache_control headers that can cause errors on models that handle caching differently. Set DISABLE_PROMPT_CACHING=1 to suppress them.
• Extended thinking — Claude Code enables reasoning by default. For models without any reasoning support, set MAX_THINKING_TOKENS=0 to disable it entirely.

Adding a Model to the Picker¶

Use ANTHROPIC_CUSTOM_MODEL_OPTION to add a single custom entry to the /model picker without replacing the built-in aliases. Useful for testing a specific Bedrock model ID alongside the standard Claude tiers:

{
  "env": {
    "ANTHROPIC_CUSTOM_MODEL_OPTION": "moonshot.kimi-k2-instruct",
    "ANTHROPIC_CUSTOM_MODEL_OPTION_NAME": "Kimi K2",
    "ANTHROPIC_CUSTOM_MODEL_OPTION_DESCRIPTION": "Moonshot Kimi K2 via stdapi.ai"
  }
}

Claude Code skips validation for this model ID, so any Bedrock model ID accepted by stdapi.ai works here.

Other Anthropic-Compatible Tools¶

Any tool using the Anthropic SDK or messages API can be configured the same way—set the ANTHROPIC_BASE_URL to https://YOUR_STDAPI_URL/anthropic and ANTHROPIC_API_KEY (or equivalent) to your stdapi.ai API key.

Running stdapi.ai Locally¶

stdapi.ai works well when running locally with Docker, making it ideal for your development environment.

API Base URL: http://localhost:8000/v1
API Key: your_stdapi_key

ANTHROPIC_BASE_URL: http://localhost:8000/anthropic
ANTHROPIC_AUTH_TOKEN: your_stdapi_key

Next Steps¶