# awslabs/agentcore-samples

Amazon Bedrock Agentcore accelerates AI agents into production with the scale, reliability, and security, critical to real-world deployment.

Repository: https://github.com/awslabs/agentcore-samples
Canonical: https://ross.abutalabs.com/products/agentcore-samples
Homepage: https://aws.amazon.com/bedrock/agentcore/
Language: Python
License: Apache-2.0
License Family: permissive
Topics: agent, agentic-ai, agents, authentication, bedrock, core, gateway, identity-management, memory-management, production-code, runtime
Last push: 2026-08-26T14:40:31+00:00

## Health v2 (maintenance only)
Score: 63/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 35, longevity 30
- inputs: {"age_days": 426, "days_push": 7, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3316, forks 1303 (observed 2026-08-28T04:07:56.127909+00:00)

## What it is
A collection of examples and tutorials for Amazon Bedrock AgentCore, AWS's platform for deploying and operating AI agents securely at scale. It demonstrates framework-agnostic, model-agnostic agent deployment covering runtime, gateway, identity, and memory capabilities.

## Use cases
- deploy ai agents to production on aws
- learn amazon bedrock agentcore with examples
- run langgraph or crewai agents on managed infrastructure
- add authentication and access control to agent tool calls
- scale ai agents without managing infrastructure
- migrate from agentcore starter toolkit to agentcore cli

## When to choose
- You are building production AI agents on AWS with any framework (Strands, CrewAI, LangGraph, LlamaIndex) and want working sample code
- You need examples of AgentCore runtime, gateway, identity, and memory integrations
- You want to learn how to deploy agents without managing specialized infrastructure

## When to avoid
- You want a runnable library or SDK itself rather than example code (use the AgentCore Python SDK or CLI instead)
- You are not deploying to AWS or do not want cloud-managed agent infrastructure
- You need fully self-hosted or vendor-neutral agent deployment

## Facets
- artifact type: learning-resource
- maturity: active
- function: agent-framework, auth, sdk, developer-tools, mcp
- domain: large-language-models, cloud-computing, developer-tools, tutorials
- platform: python, cloud
- tags: aws-bedrock, agentcore, samples, tutorials, production-ai-agents, framework-agnostic, model-agnostic, ai-agents, docker

## Member repositories
- awslabs/agentcore-samples (main) score 63

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:56.127909+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:42:04.218368+00:00, confidence not recorded.
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  - homepage: https://aws.amazon.com/bedrock/agentcore/ (fetched 2026-08-29T09:35:16.685912+00:00, sha be40da634407)
  - site_page: https://aws.amazon.com/getting-started?nc2=h_dsc_aa_gs (fetched 2026-08-29T09:35:16.697254+00:00, sha f35fd0664950)
  - site_page: https://aws.amazon.com/about-aws/global-infrastructure?nc2=h_dsc_aa_gi (fetched 2026-08-29T09:35:16.698997+00:00, sha 79a446e5fbd1)
  - site_page: https://aws.amazon.com/products/developer-tools/agent-toolkit-for-aws?nc2=h_dsc_ex_s5 (fetched 2026-08-29T09:35:16.695075+00:00, sha 3cc21b596f92)
  - site_page: https://aws.amazon.com/pricing?nc2=h_pr_hub (fetched 2026-08-29T09:35:16.701477+00:00, sha e2abd01d7981)
  - site_page: https://aws.amazon.com/savingsplans?nc2=h_pr_sp (fetched 2026-08-29T09:35:16.703358+00:00, sha 9ff3c7ad93e0)
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- Data as of 2026-08-30T08:39:29.467469+00:00.