Amazon Bedrock (Converse API) Integration with OpenClaw
Learn how to use Amazon Bedrock models via the Bedrock Converse streaming provider in OpenClaw. This guide covers AWS SDK authentication setup and configuration for developers.
Read this when
- You want to use Amazon Bedrock models with OpenClaw
- You need AWS credential/region setup for model calls
OpenClaw can use Amazon Bedrock models through its Bedrock Converse streaming provider. Bedrock authentication relies on the AWS SDK default credential chain, not an API key.
| Property | Value |
|---|---|
| Provider | amazon-bedrock |
| API | bedrock-converse-stream |
| Auth | AWS credentials (env vars, shared config, or instance role) |
| Region | AWS_REGION or AWS_DEFAULT_REGION (default: us-east-1) |
Getting started
Pick your preferred authentication method and follow the setup steps.
Access keys / env vars
Best for: developer machines, CI, or hosts where you manage AWS credentials directly.
Set AWS credentials on the gateway host
export AWS_ACCESS_KEY_ID="EXAMPLE_AWS_ACCESS_KEY_ID"
export AWS_SECRET_ACCESS_KEY="..."
export AWS_REGION="us-east-1"
# Optional:
export AWS_SESSION_TOKEN="..."
export AWS_PROFILE="your-profile"
# Optional (Bedrock API key/bearer token):
export AWS_BEARER_TOKEN_BEDROCK="..."
Add a Bedrock provider and model to your config
No apiKey is needed. Configure the provider with auth: "aws-sdk":
{
models: {
providers: {
"amazon-bedrock": {
baseUrl: "https://bedrock-runtime.us-east-1.amazonaws.com",
api: "bedrock-converse-stream",
auth: "aws-sdk",
models: [
{
id: "us.anthropic.claude-opus-4-6-v1",
name: "Claude Opus 4.6 (Bedrock)",
reasoning: true,
input: ["text", "image"],
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
contextWindow: 200000,
maxTokens: 8192,
},
],
},
},
},
agents: {
defaults: {
model: { primary: "amazon-bedrock/us.anthropic.claude-opus-4-6-v1" },
},
},
}
Verify models are available
openclaw models list
Tip
With env-marker auth (
AWS_ACCESS_KEY_ID,AWS_PROFILE, orAWS_BEARER_TOKEN_BEDROCK), OpenClaw automatically enables the implicit Bedrock provider for model discovery without extra configuration.
EC2 instance roles (IMDS)
Best for: EC2 instances with an IAM role attached, using the instance metadata service for authentication.
Enable discovery explicitly
When using IMDS, OpenClaw cannot detect AWS auth from env markers alone, so you must opt in:
openclaw config set plugins.entries.amazon-bedrock.config.discovery.enabled true
openclaw config set plugins.entries.amazon-bedrock.config.discovery.region us-east-1
Optionally add an env marker for auto mode
If you also want the env-marker auto-detection path to work (for example, for openclaw status surfaces):
export AWS_PROFILE=default
export AWS_REGION=us-east-1
You do not need a fake API key.
Verify models are discovered
openclaw models list
Warning
The IAM role attached to your EC2 instance must have the following permissions:
bedrock:InvokeModelbedrock:InvokeModelWithResponseStreambedrock:ListFoundationModels(for automatic discovery)bedrock:ListInferenceProfiles(for inference profile discovery)Or attach the managed policy
AmazonBedrockFullAccess.
Note
You only need
AWS_PROFILE=defaultif you specifically want an env marker for auto mode or status surfaces. The actual Bedrock runtime auth path uses the AWS SDK default chain, so IMDS instance-role auth works even without env markers.
Automatic model discovery
OpenClaw can automatically discover Bedrock models that support streaming
and text output. Discovery uses bedrock:ListFoundationModels and
bedrock:ListInferenceProfiles, and results are cached (default: 1 hour).
How the implicit provider is enabled:
- If
plugins.entries.amazon-bedrock.config.discovery.enabledistrue, OpenClaw will try discovery even when no AWS env marker is present. - If
plugins.entries.amazon-bedrock.config.discovery.enabledis unset, OpenClaw only auto-adds the implicit Bedrock provider when it sees one of these AWS auth markers:AWS_BEARER_TOKEN_BEDROCK,AWS_ACCESS_KEY_ID+AWS_SECRET_ACCESS_KEY, orAWS_PROFILE. - The actual Bedrock runtime auth path still uses the AWS SDK default chain, so
shared config, SSO, and IMDS instance-role auth can work even when discovery
needed
enabled: trueto opt in.
Note
For explicit
models.providers["amazon-bedrock"]entries, OpenClaw can still resolve Bedrock env-marker auth early from AWS env markers such asAWS_BEARER_TOKEN_BEDROCKwithout forcing full runtime auth loading. The actual model-call auth path still uses the AWS SDK default chain.
Discovery config options
Config options live under plugins.entries.amazon-bedrock.config.discovery:
{
plugins: {
entries: {
"amazon-bedrock": {
config: {
discovery: {
enabled: true,
region: "us-east-1",
providerFilter: ["anthropic", "amazon"],
refreshInterval: 3600,
defaultContextWindow: 32000,
defaultMaxTokens: 4096,
},
},
},
},
},
}
| Option | Default | Description |
|---|---|---|
enabled | auto | In auto mode, OpenClaw only enables the implicit Bedrock provider when it sees a supported AWS env marker. Set true to force discovery. |
region | AWS_REGION / AWS_DEFAULT_REGION / us-east-1 | AWS region used for discovery API calls. |
providerFilter | (all) | Matches Bedrock provider names (for example anthropic, amazon). |
refreshInterval | 3600 | Cache duration in seconds. Set to 0 to disable caching. |
defaultContextWindow | 32000 | Context window used for discovered models with no known token limits (override if you know your model limits). |
defaultMaxTokens | 4096 | Max output tokens used for discovered models with no known token limits (override if you know your model limits). |
Context window and max-token limits
The Bedrock ListFoundationModels and GetFoundationModel APIs return no
token-limit metadata, only model ID, name, modalities, and lifecycle
status. OpenClaw ships a lookup table of known context windows and output
limits for popular Bedrock models (Claude, Nova, Llama, Mistral, DeepSeek,
and others) so session management, compaction thresholds, and
context-overflow detection work correctly for those models.
Discovered models not in the table fall back to defaultContextWindow
and defaultMaxTokens. If a model you use is missing accurate limits,
override it with an explicit
models.providers["amazon-bedrock"].models entry.
Quick setup (AWS path)
This walkthrough creates an IAM role, attaches Bedrock permissions, associates the instance profile, and enables OpenClaw discovery on the EC2 host.
# 1. Create IAM role and instance profile
aws iam create-role --role-name EC2-Bedrock-Access \
--assume-role-policy-document '{
"Version": "2012-10-17",
"Statement": [{
"Effect": "Allow",
"Principal": {"Service": "ec2.amazonaws.com"},
"Action": "sts:AssumeRole"
}]
}'
aws iam attach-role-policy --role-name EC2-Bedrock-Access \
--policy-arn arn:aws:iam::aws:policy/AmazonBedrockFullAccess
aws iam create-instance-profile --instance-profile-name EC2-Bedrock-Access
aws iam add-role-to-instance-profile \
--instance-profile-name EC2-Bedrock-Access \
--role-name EC2-Bedrock-Access
# 2. Attach to your EC2 instance
aws ec2 associate-iam-instance-profile \
--instance-id i-xxxxx \
--iam-instance-profile Name=EC2-Bedrock-Access
# 3. On the EC2 instance, enable discovery explicitly
openclaw config set plugins.entries.amazon-bedrock.config.discovery.enabled true
openclaw config set plugins.entries.amazon-bedrock.config.discovery.region us-east-1
# 4. Optional: add an env marker if you want auto mode without explicit enable
echo 'export AWS_PROFILE=default' >> ~/.bashrc
echo 'export AWS_REGION=us-east-1' >> ~/.bashrc
source ~/.bashrc
# 5. Verify models are discovered
openclaw models list
Advanced configuration
Inference profiles
OpenClaw discovers regional and global inference profiles alongside
foundation models. When a profile maps to a known foundation model, the
profile inherits that model's capabilities (context window, max tokens,
reasoning, vision) and the correct Bedrock request region is injected
automatically. This means cross-region Claude profiles work without manual
provider overrides. Global cross-region profiles (global.*) are listed
first in openclaw models list since they generally offer better capacity
and automatic failover.
Inference profile IDs look like us.anthropic.claude-opus-4-6-v1 (regional)
or anthropic.claude-opus-4-6-v1 (global). If the backing model is already
in the discovery results, the profile inherits its full capability set;
otherwise safe defaults apply.
No extra configuration is needed. As long as discovery is enabled and the IAM
principal has bedrock:ListInferenceProfiles, profiles appear alongside
foundation models in openclaw models list.
Service tier
Some Bedrock models support a service_tier parameter to optimize for cost
or latency. The following tiers are available:
| Tier | Description |
|---|---|
default | Standard Bedrock tier |
flex | Discounted processing for workloads that can tolerate longer latency |
priority | Prioritized processing for latency-sensitive workloads |
reserved | Reserved capacity for steady-state workloads |
Set serviceTier (or service_tier) via agents.defaults.params for
Bedrock model requests, or per-model in
agents.defaults.models["<model-key>"].params:
{
agents: {
defaults: {
params: {
serviceTier: "flex", // applies to all models
},
models: {
"amazon-bedrock/mistral.mistral-large-3-675b-instruct": {
params: {
serviceTier: "priority", // per-model override
},
},
},
},
},
}
Valid values are default, flex, priority, and reserved. Claude
Fable 5, Opus 5, and Sonnet 5 only support the default tier; OpenClaw warns and
ignores flex, priority, or reserved requested for those models. For
other models, not every model supports every tier -- an unsupported tier
returns a Bedrock validation error, and the error message can be
misleading (for example "The provided model identifier is invalid"
rather than naming the tier as the problem). If you see this error, check
whether the model supports the requested tier.
Claude Opus 5, 4.8, and 4.7 temperature
Bedrock rejects the temperature parameter for Claude Opus 5, Opus 4.8,
and Opus 4.7. OpenClaw omits temperature automatically for any matching Bedrock
ref, including foundation model ids, named inference profiles, application
inference profiles whose underlying model resolves to Opus 5/4.8/4.7 via
bedrock:GetInferenceProfile, and dotted opus-4.7/opus-4.8 variants
with optional region prefixes (us., eu., ap., apac., au., jp.,
global.). No config knob is required, and the omission applies to both
the request options object and the inferenceConfig payload field.
Claude Opus 5
Use amazon-bedrock/anthropic.claude-opus-5 on the Messages-API Bedrock
endpoint, or a regional/global inference profile such as
global.anthropic.claude-opus-5 when it appears in Bedrock discovery.
OpenClaw applies the 1,000,000-token context window, 128,000-token output
limit, image input, prompt caching, refusal-safe streaming, and native
xhigh/max effort levels.
Adaptive thinking defaults to high. /think off disables thinking, while
/think xhigh|max keeps adaptive thinking enabled. OpenClaw omits custom
sampling parameters and unsupported non-default service tiers.
Claude Fable 5
Use amazon-bedrock/anthropic.claude-fable-5 in us-east-1, or the
regional inference ids such as us.anthropic.claude-fable-5.
OpenClaw applies Fable's 1M context window, 128K output limit, always-on
adaptive thinking, and supported effort mapping. /think off and
/think minimal map to low; temperature and forced tool choice controls
are omitted, matching the Opus 4.7/4.8 route. Streaming output is held
until Bedrock returns a terminal status so mid-stream refusals do not
expose partial text.
AWS requires an explicit provider_data_share data-retention opt-in before
Fable is available. Prompts and completions are shared with Anthropic and
retained for up to 30 days for trust and safety. Review and configure
Bedrock data retention
before enabling the model.
Claude Mythos 5
Claude Mythos 5 is accessible through Bedrock only for accounts that have obtained the necessary limited-access approval. OpenClaw recognizes the foundation model anthropic.claude-mythos-5 and regional or global inference profiles like us.anthropic.claude-mythos-5.
OpenClaw applies the 1,000,000-token context window, 128,000-token output limit, image input, prompt caching, refusal-safe streaming, and native effort levels. Adaptive thinking is always enabled: /think off and /think minimal map to low, while xhigh and max remain available. Custom sampling and forced tool choice values are omitted.
Claude Sonnet 5
AWS documents Sonnet 5 for both the bedrock-runtime and bedrock-mantle endpoints. OpenClaw recognizes the Bedrock foundation model anthropic.claude-sonnet-5 and regional or global inference profiles such as us.anthropic.claude-sonnet-5. It applies the 1,000,000-token context window, 128,000-token output limit, image input, native effort levels, prompt caching, and refusal-safe streaming.
Bedrock keeps adaptive thinking enabled for Sonnet 5. OpenClaw defaults to high; /think off and /think minimal map to low because this route cannot disable thinking. Custom temperature and forced tool choice values are omitted while adaptive thinking is active.
Guardrails
You can attach Amazon Bedrock Guardrails to any Bedrock model invocation by including a guardrail object in the amazon-bedrock plugin config. Guardrails allow you to enforce content filtering, topic denial, word filters, sensitive information filters, and contextual grounding checks.
{
plugins: {
entries: {
"amazon-bedrock": {
config: {
guardrail: {
guardrailIdentifier: "abc123", // guardrail ID or full ARN
guardrailVersion: "1", // version number or "DRAFT"
streamProcessingMode: "sync", // optional: "sync" or "async"
trace: "enabled", // optional: "enabled", "disabled", or "enabled_full"
},
},
},
},
},
}
guardrailIdentifier and guardrailVersion are required.
| Option | Description |
|---|---|
guardrailIdentifier | Guardrail ID (e.g. abc123) or full ARN (e.g. arn:aws:bedrock:us-east-1:123456789012:guardrail/abc123). |
guardrailVersion | Published version number, or "DRAFT" for the working draft. |
streamProcessingMode | "sync" or "async" for guardrail evaluation during streaming. If omitted, Bedrock uses its default. |
trace | "enabled" or "enabled_full" for debugging; omit or set "disabled" for production. |
Warning
The IAM principal used by the gateway must have the
bedrock:ApplyGuardrailpermission in addition to the standard invoke permissions.
Embeddings for memory search
Bedrock can also act as the embedding provider for memory search. This is configured separately from the inference provider. Set memory.search.provider to "bedrock":
{
memory: {
search: {
provider: "bedrock",
model: "amazon.titan-embed-text-v2:0", // default
},
},
}
Bedrock embeddings use the same AWS SDK credential chain as inference (instance roles, SSO, access keys, shared config, and web identity). No API key is required.
Supported embedding models include Amazon Titan Embed (v1, v2), Amazon Nova Embed, Cohere Embed (v3, v4), and TwelveLabs Marengo. See Memory configuration reference -- Bedrock for the full model list and dimension options.
Notes and caveats
- Bedrock requires model access enabled in your AWS account/region.
- Automatic discovery needs the
bedrock:ListFoundationModelsandbedrock:ListInferenceProfilespermissions. - If you rely on auto mode, set one of the supported AWS auth env markers on the gateway host. If you prefer IMDS/shared-config auth without env markers, set
plugins.entries.amazon-bedrock.config.discovery.enabled: true. - OpenClaw surfaces the credential source in this order:
AWS_BEARER_TOKEN_BEDROCK, thenAWS_ACCESS_KEY_ID+AWS_SECRET_ACCESS_KEY, thenAWS_PROFILE, then the default AWS SDK chain. - Reasoning support depends on the model; check the Bedrock model card for current capabilities.
- If you prefer a managed key flow, you can also place an OpenAI-compatible proxy in front of Bedrock and configure it as an OpenAI provider instead.
Related
-
Model selection, Choosing providers, model refs, and failover behavior.
-
Memory search, Bedrock embeddings for memory search configuration.
-
Memory config reference, Full Bedrock embedding model list and dimension options.
-
Troubleshooting, General troubleshooting and FAQ.