Agent Frameworks
May 13, 2026 ยท View on GitHub
AgentCore CLI supports multiple agent frameworks for template-based agent creation, plus a BYO (Bring Your Own) option for existing code.
Supported Languages
| Language | Supported Frameworks | Runtime | Notes |
|---|---|---|---|
| Python | All frameworks | Python 3.12+ | Default language. Uses uv for dependency management. |
| TypeScript | Strands, Vercel AI | Node 22 | Uses npm + tsx for the dev loop. Other frameworks are not yet available in TS. |
Pass --language TypeScript to agentcore create or agentcore add agent to scaffold a TypeScript project. The
framework is restricted to Strands or VercelAI; other values are rejected. See
Local Development for the TS dev loop.
Available Frameworks
| Framework | Supported Model Providers |
|---|---|
| Strands Agents | Bedrock, Anthropic, OpenAI, Gemini |
| LangChain_LangGraph | Bedrock, Anthropic, OpenAI, Gemini |
| GoogleADK | Gemini only |
| OpenAIAgents | OpenAI only |
| VercelAI | Bedrock, Anthropic, OpenAI, Gemini |
Framework Selection Guide
Strands Agents
AWS's native agent framework designed for Amazon Bedrock.
Best for:
- Projects primarily using Amazon Bedrock models
- Integration with AWS services
- Production deployments on AWS infrastructure
Model providers: Bedrock, Anthropic, OpenAI, Gemini
Languages: Python, TypeScript
agentcore create --framework Strands --model-provider Bedrock
# TypeScript variant
agentcore create --framework Strands --model-provider Bedrock --language TypeScript
LangChain / LangGraph
Popular open-source framework with extensive ecosystem.
Best for:
- Complex multi-step agent workflows
- Projects requiring LangChain's extensive tool ecosystem
- Teams already familiar with LangChain
Model providers: Bedrock, Anthropic, OpenAI, Gemini
agentcore create --framework LangChain_LangGraph --model-provider Anthropic
GoogleADK
Google's Agent Development Kit.
Best for:
- Projects using Google's Gemini models
- Integration with Google Cloud services
Model providers: Gemini only
agentcore create --framework GoogleADK --model-provider Gemini
OpenAIAgents
OpenAI's native agent framework.
Best for:
- Projects using OpenAI models exclusively
- Simple agent workflows with OpenAI's function calling
Model providers: OpenAI only
agentcore create --framework OpenAIAgents --model-provider OpenAI --api-key sk-...
Vercel AI SDK
Vercel's AI SDK for building AI-powered applications.
Best for:
- Full-stack AI applications with streaming support
- Projects using Vercel's ecosystem
- TypeScript-first agent development
Model providers: Bedrock, Anthropic, OpenAI, Gemini
Languages: Python, TypeScript
agentcore create --framework VercelAI --model-provider Bedrock
# TypeScript variant
agentcore create --framework VercelAI --model-provider Bedrock --language TypeScript
Import from Bedrock Agents
If you have an existing Bedrock Agent, you can import its configuration and translate it into runnable Strands or LangChain/LangGraph code. The imported agent preserves your Bedrock Agent's action groups, knowledge bases, multi-agent collaboration, guardrails, prompts, and memory configuration.
# Interactive (select "Import from Bedrock Agents" in the wizard)
agentcore add agent
# Non-interactive
agentcore add agent \
--name MyAgent \
--type import \
--agent-id AGENT123 \
--agent-alias-id ALIAS456 \
--region us-east-1 \
--framework Strands \
--memory none
What gets imported
The import process fetches your Bedrock Agent's full configuration and translates it into framework-specific Python code that runs on AgentCore:
- Action groups (function-schema and built-in) become
@tooldecorated functions - Knowledge bases become retrieval tool integrations
- Multi-agent collaboration produces separate collaborator files with recursive translation
- Code interpreter wires to AgentCore's
code_interpreter_client - Guardrails are configured in the model initialization
- Prompt overrides are preserved as template variables
- Memory integrates with AgentCore's memory service when enabled
Import options
| Flag | Description |
|---|---|
--type import | Use import mode (required) |
--agent-id <id> | Bedrock Agent ID |
--agent-alias-id <id> | Bedrock Agent Alias ID |
--region <region> | AWS region where the Bedrock Agent exists |
--framework <fw> | Strands or LangChain_LangGraph |
--memory <opt> | none, shortTerm, longAndShortTerm |
Bring Your Own (BYO) Agent
For existing agent code or frameworks not listed above, use the BYO option:
agentcore add agent \
--name MyAgent \
--type byo \
--code-location ./my-agent \
--entrypoint main.py \
--language Python
BYO Requirements
- Entrypoint: Your code must expose an HTTP endpoint that accepts agent invocation requests
- Code location: Directory containing your agent code
- Language: Python
BYO Options
| Flag | Description |
|---|---|
--type byo | Use BYO mode (required) |
--code-location <path> | Directory containing your agent code |
--entrypoint <file> | Entry file (e.g., main.py or index.ts) |
--language <lang> | Python |
Framework Comparison
| Feature | Strands | LangChain | GoogleADK | OpenAIAgents | VercelAI |
|---|---|---|---|---|---|
| Multi-provider support | Yes | Yes | No | No | Yes |
| AWS Bedrock native | Yes | No | No | No | No |
| Tool ecosystem | Growing | Extensive | Moderate | Moderate | Moderate |
| Memory integration | Native | Via libs | Via libs | Via libs | Via libs |
Protocol Compatibility
Not all frameworks support all protocol modes. MCP protocol is a standalone tool server with no framework.
| Protocol | Supported Frameworks |
|---|---|
| HTTP | Strands, LangChain_LangGraph, GoogleADK, OpenAIAgents, VercelAI |
| MCP | None (standalone tool server) |
| A2A | Strands, GoogleADK, LangChain_LangGraph |