AWS Bedrock AgentCore alternatives in 2026

Amazon Bedrock AgentCore is AWS’s kit for running the agent you write: each session gets its own microVM, and you add Memory, Gateway, Identity, a Code Interpreter, and a Browser as you need them. It runs any framework and any model, and it carries the longest compliance list in this category.

Its differences are about who does the work. You write and deploy the agent code yourself, you add the parts you need, and you pay per vCPU-hour. So the usual reason to look elsewhere is a team that doesn’t want to write the loop at all, wants its OpenAPI document to become the tools, or wants one price per model call.

Every fact below comes from the vendors’ own docs and pricing pages, checked on September 28, 2026.

What AgentCore does well

• Any framework, any model. Runtime “works with custom frameworks and any open-source framework, including CrewAI, LangGraph, LlamaIndex, Google ADK, OpenAI Agents SDK, and Strands Agents”, and with models from Bedrock, OpenAI, Gemini, Claude, and more.
• Compliance. “HIPAA eligible and FedRAMP (Class C and Class D), SOC 2 and ISO”, plus VPC and PrivateLink connections.
• Pay per second of use. Runtime is $0.0895 per vCPU-hour and $0.00945 per GB-hour on v1 microVMs, with “no upfront commitments or minimum fees.” AWS’s worked example, a support agent with 1 million sessions a month, comes to $6,703.
• Parts you’d otherwise build. With Gateway, an OpenAPI target (or a Smithy model, or a Lambda function) becomes MCP tools ($0.005 per 1,000 calls). The Code Interpreter runs Python, JavaScript, and TypeScript in a sandbox. Memory stores events and long-term records.
• Regions. Runtime, Gateway, and the built-in tools (Code Interpreter and Browser) run in all seven European regions on AWS’s table, including Frankfurt, Ireland (eu-west-1), London (eu-west-2), and Paris (eu-west-3), and in AWS GovCloud (US-West).

Where it stops

1. You write the loop. AgentCore hosts your agent’s code. The loop, the prompts, the tool routing, and the stream to your UI stay yours. (The Strands-based harness is the exception, and it’s the one with the approval hook.)
2. Sessions and users are yours to map. AgentCore doesn’t track which session belongs to which user. AWS says “your client backend should maintain the relationship between users and their session IDs.”
3. The bill has several meters. AgentCore bills vCPU-hours and GB-hours by the second, plus Gateway, Memory, and the built-in tools as you use them.

The alternatives

So where do you go when you don’t want to write the loop, or you want your own API as the tools?

Claude Managed Agents

Anthropic runs the loop and the sandbox, and a tool set to always_ask waits for your confirmation before it runs. You pay $0.08 per session-hour only while the session is running, plus tokens. The trade: it runs Claude models only. Claude Managed Agents alternatives covers it in depth.

LangSmith Deployment

Also hosts the agent you write, and its approvals are LangGraph interrupts. Deployments run in LangChain’s cloud in the US or the EU. Plus is $39 a seat a month plus metered runtime at $0.0675 per vCPU-hour. Self-hosting is an add-on to the Enterprise plan.

OpenAI’s Agents API

A managed harness from OpenAI, with sessions, compaction, and recovery. It has no approval step of its own. Pricing is model tokens, tools, and $0.03 per 20 minutes for a 1 GB sandbox.

Cadenya

Cadenya runs the loop for you, so there’s no agent code to deploy. You point a tool set at your OpenAPI document, pick any model from a provider you connect, and start an objective, with approvals set per tool set. It’s free for 1,000 loops a month and $49 for 50,000. What it offers that AgentCore doesn’t is at the end.

Your own loop on a durable engine

If you want to write the loop and keep each step durable, run it yourself on Temporal, Restate, DBOS, or Inngest. DBOS vs Temporal is a good first read if your app already runs on Postgres.

Side by side

	Amazon Bedrock AgentCore	Claude Managed Agents	LangSmith Deployment	OpenAI Agents API	Cadenya
Who writes the loop	You	Anthropic	You	OpenAI	Cadenya, configured by you
Approvals	A harness hook that calls a Lambda function	always_ask per tool	LangGraph interrupts	No approval step	Set per tool set, answered from your backend, a webhook, or the React widget
Models	Any	Claude	Any your code calls	OpenAI	Any provider you connect
Starting price	Per second, no minimum	$0.08 per running hour, plus tokens	$39 a seat a month, plus runtime	Tokens and sandbox time	$0 for 1,000 loops

When to stay on AgentCore

Stay if you’re on AWS, you write the agent anyway, and the compliance list matters.

What does Cadenya offer that AgentCore doesn’t?

AgentCore hosts the agent you write, on AWS. Cadenya runs the agent for you: the loop, its durable state, and its human-in-the-loop approvals, with no code to deploy. Here’s what that covers:

1. The agent loop, already written. AgentCore Runtime runs your code in a microVM per session, and the loop, the prompts, the tool routing, and the stream to your UI stay yours. On Cadenya you configure the agent on a variation, and Cadenya calls the model, runs the tools, streams each reply, and compacts the context window when a conversation gets long.
2. One service instead of a kit. There’s no agent code to deploy, no vCPUs or memory to size, and no AWS account to set up. Where AgentCore splits the job into Runtime, Memory, Gateway, and Identity, Cadenya is one API.
3. Human-in-the-loop approvals, screen included. A tool marked for approval pauses the objective on toolApprovalRequested until your backend, a webhook handler that posts to Slack, or a person in the React chat widget approves or denies it. A denial can carry a memo that steers the agent.
4. Users mapped to conversations. AgentCore “does not enforce session-to-user mappings”, so your backend tracks them. On Cadenya, your backend mints a widget session per user, and Cadenya derives the tenant, the user, the secrets, and the pinned parameters from it. The session can carry the user’s short-lived token as a secret that overrides the shared API credential, so your API sees the signed-in user on each tool call.
5. Your OpenAPI document as the tools, with no per-call fee. Gateway turns an OpenAPI target into MCP tools at $0.005 per 1,000 calls. A Cadenya tool set turns every operation into a tool, re-checks the document each hour, filters the list, and loads tools on demand, and tool calls aren’t billed.
6. A price in one line. AgentCore bills vCPU-hours and GB-hours by the second, plus Gateway, Memory, and the built-in tools as you use them. Cadenya bills per loop, one LLM request: free for 1,000 a month, $49 a month for 50,000, then $0.0015 each.

How objectives work walks through an agent turn on Cadenya, and the free plan needs no card.

No account yet? A coding agent can create a temporary workspace with cadenya workspaces create --temporary, run its first objectives there, and hand you a link to claim it, as auth.md explains. To create an account, sign up at app.cadenya.com/signup, then copy your API key from the API keys page at app.cadenya.com/account/apiKeys.