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Aws Agentcore Langgraph

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by killerapp

Multi-agent systems on AWS Bedrock AgentCore with LangGraph orchestration. Source: https://github.com/aws/bedrock-agentcore-starter-toolkit ```bash pip install bedrock-agentcore bedrock-agentcore-starter-toolkit langgraph uv tool install bedrock-agentcore-starter-toolkit # installs agentcore CLI ``` ```python from langgraph.graph import StateGraph, START from langgraph.graph.message import add_messages from langgraph.prebuilt import ToolNode, tools_condition # routing + tool execution from bedro

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AWS AgentCore + LangGraph

Multi-agent systems on AWS Bedrock AgentCore with LangGraph orchestration. Source: https://github.com/aws/bedrock-agentcore-starter-toolkit

Install

pip install bedrock-agentcore bedrock-agentcore-starter-toolkit langgraph
uv tool install bedrock-agentcore-starter-toolkit  # installs agentcore CLI

Quick Start

from langgraph.graph import StateGraph, START
from langgraph.graph.message import add_messages
from langgraph.prebuilt import ToolNode, tools_condition  # routing + tool execution
from bedrock_agentcore.runtime import BedrockAgentCoreApp
from typing import Annotated
from typing_extensions import TypedDict

class State(TypedDict):
    messages: Annotated[list, add_messages]

builder = StateGraph(State)
builder.add_node("agent", agent_node)
builder.add_node("tools", ToolNode(tools))  # prebuilt tool executor
builder.add_conditional_edges("agent", tools_condition)  # routes to tools or END
builder.add_edge(START, "agent")
graph = builder.compile()

app = BedrockAgentCoreApp()  # Wraps as HTTP service on port 8080 (/invocations, /ping)
@app.entrypoint
def invoke(payload, context):
    result = graph.invoke({"messages": [("user", payload.get("prompt", ""))]})
    return {"result": result["messages"][-1].content}
app.run()

CLI Commands

| Command | Purpose |

|---------|---------|

| agentcore configure -e agent.py --region us-east-1 | Setup |

| agentcore configure -e agent.py --region us-east-1 --name my_agent --non-interactive | Scripted setup |

| agentcore launch --deployment-type container | Deploy (container mode) |

| agentcore launch --disable-memory | Deploy without memory subsystem |

| agentcore dev | Hot-reload local dev server |

| agentcore invoke '{"prompt": "Hello"}' | Test |

| agentcore destroy | Cleanup |

Core Patterns

Multi-Agent Orchestration

  • Orchestrator delegates to specialists (customer service, e-commerce, healthcare, financial, etc.)
  • Specialists: inline functions or separate deployed agents; all share session_id for context

Memory (STM/LTM)

from bedrock_agentcore.memory import MemoryClient
memory = MemoryClient()
memory.create_event(session_id, actor_id, event_type, payload)  # Store
events = memory.list_events(session_id)  # Retrieve (returns list)
  • STM: Turn-by-turn within session | LTM: Facts/decisions across sessions/agents
  • ~10s eventual consistency after writes

Gateway Tools

python -m bedrock_agentcore.gateway.deploy --stack-name my-agents --region us-east-1
from bedrock_agentcore.gateway import GatewayToolClient
gateway = GatewayToolClient()
result = gateway.call("tool_name", param1=value1, param2=value2)
  • Transport: Fallback Mock (local), Local MCP servers, Production Gateway (Lambda/REST/MCP)
  • Auto-configures BEDROCK_AGENTCORE_GATEWAY_URL after deploy

Decision Tree

Multiple agents coordinating? → Orchestrator + specialists pattern
Persistent cross-session memory? → AgentCore Memory (not LangGraph checkpoints)
External APIs/Lambda? → AgentCore Gateway
Single agent, simple? → Quick Start above
Complex multi-step logic? → StateGraph + tools_condition + ToolNode

Key Concepts

  • AgentCore Runtime: HTTP service on port 8080 (handles /invocations, /ping)
  • AgentCore Memory: Managed cross-session/cross-agent memory
  • LangGraph Routing: tools_condition for agent→tool routing, ToolNode for execution
  • AgentCore Gateway: Transforms APIs/Lambda into MCP tools with auth

Naming Rules

  • Start with letter, only letters/numbers/underscores, 1-48 chars: my_agent not my-agent

Troubleshooting

| Issue | Fix |

|-------|-----|

| on-demand throughput isn't supported | Use us.anthropic.claude-* inference profiles |

| Model use case details not submitted | Fill Anthropic form in Bedrock Console |

| Invalid agent name | Use underscores not hyphens |

| Memory empty after write | Wait ~10s (eventual consistency) |

| Container not reading .env | Set ENV in Dockerfile, not .env |

| Memory not working after deploy | Check logs for "Memory enabled/disabled" |

| list_events returns empty | Check actor_id/session_id match; event['payload'] is a list |

| Gateway "Unknown tool" | Lambda must strip ___ prefix from bedrockAgentCoreToolName |

| Platform mismatch warning | Normal - CodeBuild handles ARM64 cross-platform builds |

References