mastra-bedrock

name	mastra-bedrock
description	Use Amazon Bedrock as the model provider for a Mastra agent, and deploy Mastra agents to AWS Bedrock AgentCore. Use when someone wants a Mastra agent to run on Bedrock/AWS, mentions Claude on Bedrock, createAmazonBedrock, fromNodeProviderChain, or AgentCore deployment.
license	Apache-2.0

Mastra + Amazon Bedrock

Wire a Mastra agent to Amazon Bedrock, and deploy it to AWS Bedrock AgentCore.

Verify before writing code

This builds on the mastra skill's rule: never trust cached Mastra API knowledge. Confirm the installed @mastra/core version and, when a model ID matters, that the model is enabled in the target Bedrock account/region.

Bedrock is not in Mastra's model router

Mastra's "provider/model" string router has no Bedrock provider — do not guess a bedrock/... string. Bedrock is used the other supported way: pass an AI SDK provider instance as the agent's model. MastraModelConfig accepts LanguageModelV1–V4, which the AI SDK Bedrock provider satisfies.

npm install @ai-sdk/amazon-bedrock @aws-sdk/credential-providers

Use the default credential chain

Build the provider with fromNodeProviderChain(). This is the load-bearing choice: the credential chain resolves credentials the standard AWS way — env vars, shared config (~/.aws), SSO, and the container/EC2/AgentCore execution role. The same code runs unchanged locally and deployed — locally it uses your AWS CLI session; on AgentCore it uses the runtime's IAM role. No key branching, no code diff between environments.

import { Agent } from '@mastra/core/agent';
import { createAmazonBedrock } from '@ai-sdk/amazon-bedrock';
import { fromNodeProviderChain } from '@aws-sdk/credential-providers';

const bedrock = createAmazonBedrock({
  credentialProvider: fromNodeProviderChain(),
});

export const agent = new Agent({
  id: 'my-agent',
  name: 'My Agent',
  instructions: '...',
  model: bedrock('us.anthropic.claude-opus-4-5-20251101-v1:0'),
});

Do not hardcode accessKeyId/secretAccessKey in the constructor, and do not set region there — the chain and the SDK read it from the environment.

Region must match the model-id prefix

Bedrock Claude models are called through cross-region inference profiles whose ID carries a region prefix — us., eu., jp., or global.. AWS_REGION must belong to that prefix's group (e.g. us.anthropic.claude-opus-4-5-20251101-v1:0 needs a us-* region). A mismatch is a runtime failure, not a type error.

Set AWS_REGION in the environment (.env locally, the Dockerfile/AgentCore config when deployed). Confirm the exact current Opus model ID against AWS docs or the @ai-sdk/amazon-bedrock model tables before committing to it — IDs change.

Local credentials

For npm run dev, the chain needs an active AWS session. Two common .env shapes:

# Named profile (~/.aws/credentials or SSO) — the chain reads the profile, not keys
AWS_PROFILE=your-profile
AWS_REGION=us-east-1

# Static keys
AWS_ACCESS_KEY_ID=your-access-key-id
AWS_SECRET_ACCESS_KEY=your-secret-access-key
AWS_REGION=us-east-1

With a profile you do not set the key vars — the two are alternatives. AWS_REGION is required either way. For SSO, aws sso login first. Also confirm the model has access enabled in the Bedrock console for that account and region.

Deploying to AgentCore

For the full deploy to AWS Bedrock AgentCore — project scaffold, bedrock-agentcore handler, Dockerfile, storage-removal gotcha, and CLI commands — see deploy-agentcore.md.