Amazon Bedrock Runtime API

Name: Amazon Bedrock Runtime API API
Brand: Amazon Bedrock Runtime API
Availability: InStock

★ Only Publicly Available SpecAI/MLLanguage ModelsapiKey5 EndpointsREST

For Agents

Invoke Amazon Bedrock foundation models for text generation, chat, and tool-use, with streaming and a unified Converse interface across providers, plus Guardrails for safety.

Quickstart

Get started with Amazon Bedrock Runtime API in minutes using your preferred integration method.

# Add to your MCP client config (Claude Desktop, Cursor, Windsurf)
{
  "jentic": {
    "url": "https://api.jentic.com/mcp",
    "auth": "oauth"
  }
}

# Then ask your agent:
"generate a chat completion with Claude on Amazon Bedrock"

# → Jentic returns the GET /events tool with parameter schema, agent executes.

Capabilities

What an agent can do with Amazon Bedrock Runtime API API.

Invoke any Amazon Bedrock-hosted foundation model with a model-specific JSON body via InvokeModel

Stream tokens incrementally with InvokeModelWithResponseStream for chat UIs and progressive output

Use the unified Converse API to run multi-turn chat across Anthropic, Meta, Mistral, Cohere, and Amazon models without rewriting the request body

Stream Converse responses with ConverseStream including token-by-token deltas and tool-use events

GET STARTED

Start building with Amazon Bedrock Runtime API API

Explore with Jentic

View OpenAPI Spec

Jentic publishes the only available OpenAPI specification for Amazon Bedrock Runtime API, keeping it validated and agent-ready.

Jentic publishes the only available OpenAPI specification for Amazon Bedrock Runtime API, keeping it validated and agent-ready. Amazon Bedrock Runtime is the inference plane of Amazon Bedrock, AWS's managed service for foundation models from Anthropic, AI21, Cohere, Meta, Mistral, Stability, and Amazon's own Titan and Nova families. The runtime API lets you invoke a model with a request body in the model's native format, stream tokens as they are generated, run a unified Converse loop across providers, and apply Bedrock Guardrails to inputs and outputs for safety filtering.

Use Cases

Patterns agents use Amazon Bedrock Runtime API API for, with concrete tasks.

★ Cross-Provider Chat with Converse

Build a chat product that can swap between Claude, Llama, Mistral, and Amazon Nova without rewriting the request body for each provider. The Converse API normalises messages, system prompts, and tool definitions into one schema; the runtime handles each provider's idiosyncratic format internally. Switching providers becomes a model-id change rather than a code change.

Call Converse on modelId=anthropic.claude-3-5-sonnet-20241022-v2:0 with messages=[{role: 'user', content: [{text: 'Summarise: ...'}]}] and inferenceConfig={maxTokens: 1024, temperature: 0.2}.

Streaming Chat UI

Power a chat interface where tokens render as the model produces them rather than waiting for the full response. ConverseStream emits messageStart, contentBlockDelta, and messageStop events that the front end consumes via SSE or WebSocket. Combined with low-latency models like Claude Haiku or Nova Micro, this delivers sub-second time-to-first-token for end users.

Call ConverseStream on modelId=anthropic.claude-3-haiku-20240307-v1:0 with the user's message, forwarding each contentBlockDelta event to the connected browser over WebSocket.

Guardrail-Filtered Customer Chatbot

Wrap a customer-facing chatbot with Bedrock Guardrails so the model never returns disallowed content, leaks PII, or strays off the policy-defined topic list. ApplyGuardrail evaluates input text against the configured Guardrail and returns an action (NONE, GUARDRAIL_INTERVENED) plus the redacted output. Combine with Converse so model calls already inherit Guardrail enforcement.

Call ApplyGuardrail with guardrailIdentifier=gr-7abc, guardrailVersion=DRAFT, source=INPUT, and content=[{text: {text: 'user message ...', qualifiers: ['guard_content']}}].

Agent Tool-Use with Claude on Bedrock

Let an AI agent use tools, such as searching a database, calling a payment API, or posting to a Slack channel, through Claude on Bedrock with Anthropic's structured tool-use schema. The agent sends tool definitions in the Converse request, Claude returns toolUse content blocks, the agent executes them via Jentic, and feeds toolResult content blocks back. Jentic handles credential isolation for both the Bedrock call and the downstream tool calls.

Call Converse on modelId=anthropic.claude-3-5-sonnet-20241022-v2:0 with toolConfig.tools=[<schemas loaded from Jentic>] and the user's request, then execute each toolUse content block via Jentic and pass the toolResult back in the next Converse call.

Key Endpoints

5 endpoints — jentic publishes the only available openapi specification for amazon bedrock runtime api, keeping it validated and agent-ready.

METHOD

PATH

DESCRIPTION

POST

/model/{modelId}/invoke

Invoke a foundation model with a provider-native body

POST

/model/{modelId}/invoke-with-response-stream

Invoke a model with streaming response

POST

/model/{modelId}/converse

Run a unified Converse multi-turn chat call

POST

/model/{modelId}/converse-stream

Run a streaming Converse call

POST

/guardrail/{guardrailIdentifier}/version/{guardrailVersion}/apply

Apply a Guardrail to text input or output

POST

/model/{modelId}/invoke

Invoke a foundation model with a provider-native body

POST

/model/{modelId}/invoke-with-response-stream

Invoke a model with streaming response

POST

/model/{modelId}/converse

Run a unified Converse multi-turn chat call

POST

/model/{modelId}/converse-stream

Run a streaming Converse call

POST

/guardrail/{guardrailIdentifier}/version/{guardrailVersion}/apply

Apply a Guardrail to text input or output

Why though Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

AWS access key ID and secret access key for Amazon Bedrock Runtime API are stored encrypted in the Jentic vault. Agents receive scoped, short-lived signing credentials and the raw IAM secrets never enter the agent context. Jentic computes the AWS Signature Version 4 signature server-side for every request.

Intent-based discovery

Agents search Jentic by intent (for example, 'generate a chat completion with Claude') and Jentic returns matching Amazon Bedrock Runtime API operations with their input schemas, the correct AWS service endpoint, and the required IAM action, so the agent can invoke the right call without crawling the AWS docs.

Time to first call

Direct Amazon Bedrock Runtime API integration: 1-3 days for AWS SDK setup, IAM role configuration, Sigv4 signing, and error handling. Through Jentic: under 1 hour, search, load schema, execute.

Related APIs

Alternatives and complements available in the Jentic catalogue.

Alternative

OpenAI API

Direct OpenAI access for GPT-4 and GPT-4o-class models with native function calling and JSON mode.

Choose the OpenAI API when the agent needs OpenAI-only models or features; choose Bedrock for AWS-native auth, data residency, and provider choice in a single API.

Alternative

Anthropic Messages API

Direct Anthropic access to Claude models with the same Messages schema Bedrock Converse adopted.

Choose Anthropic directly when the deployment is outside AWS and you want the latest Claude features earliest; choose Bedrock for AWS-region deployment and unified billing.

Complementary

Amazon SageMaker

Train, fine-tune, and host custom models for cases the foundation models on Bedrock cannot cover.

Use SageMaker when the agent needs a custom-trained model or a model not available on Bedrock; use Bedrock Runtime for the managed foundation model catalog.

FAQs

Specific to using Amazon Bedrock Runtime API API through Jentic.

Why is there no official OpenAPI spec for Amazon Bedrock Runtime API?

AWS does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call Amazon Bedrock Runtime API via structured tooling. It is validated against the live API and kept up to date. Get started at https://app.jentic.com/sign-up.

What authentication does the Amazon Bedrock Runtime API use?

All requests are signed with AWS Signature Version 4 using an AWS access key ID and secret access key. Through Jentic, the credentials live encrypted in the vault and Jentic computes the signature server-side, so the agent only ever holds a scoped Jentic credential reference.

Which models can I invoke through this API?

Any model your account has access to in Amazon Bedrock, including Anthropic Claude, Meta Llama, Mistral, Cohere Command, AI21 Jurassic, Stability SDXL, and Amazon Titan and Nova families, identified by its modelId (for example anthropic.claude-3-5-sonnet-20241022-v2:0). Access must be enabled per model in the Bedrock console first.

How do I stream tokens from a Bedrock model through Jentic?

Search Jentic for 'stream a chat completion from Bedrock', load the ConverseStream schema, and execute it. The operation maps to POST /model/{modelId}/converse-stream and Jentic forwards the AWS event stream so the agent receives messageStart, contentBlockDelta, and messageStop events as they arrive.

What are the rate limits for the Amazon Bedrock Runtime API?

Bedrock applies per-model and per-account quotas measured in requests per minute and tokens per minute (for input and output separately). Limits vary by model and region; on-demand and provisioned throughput modes have different ceilings, and ThrottlingException is returned when a quota is exceeded.

Is Amazon Bedrock free to use?

Bedrock charges per token for on-demand inference, with separate input and output token rates per model, plus optional Provisioned Throughput pricing for guaranteed capacity. There is no monthly subscription; you pay only for the tokens consumed plus any Guardrails policy units you apply.