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Integrations, memory stores, and a redesigned dashboard

This is our biggest update since launch. Omnara now connects to Slack, Discord, and GitHub, agents can keep files in shared memory stores, and the dashboard has been redesigned. Examples are now agents you deploy with your coding agent, and four more sandbox providers are available.

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Slack, Discord, and GitHub integrations

Create an integration from a project’s Integrations page, connect your account, and choose which agent profiles it can launch. In Slack and Discord, mention the bot to start an agent in a thread, or message it directly in Slack. The agent replies in the thread, can ask questions or request approvals there, and schedules can start new threads on a timer. On GitHub, an agent can launch when a pull request opens or someone mentions it. It then receives that PR’s comments, reviews, and commits, can read the diff, comment, and submit reviews, and can use Git over HTTPS with your GitHub App’s access. See Integrations.

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Memory stores

Create a memory store in a project and attach it to agents with read or read-write access. Agents read and write its files at /memory/<store-name>/ with the file tools, so they can keep notes between conversations or share files with other agents. Manage stores and files from the new Memory page, the API, or omnara memory-stores. See Memory stores.

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Redesigned dashboard

A new sidebar that adapts to where you are, redesigned agent and profile pages, an improved overview, and simpler dialogs for model providers, models, and machine pools.

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Deploy example agents with your coding agent

Each example is an agent.yaml and a SKILL.md. Ask your coding agent to read the skill and it sets the agent up with the omnara CLI: signing in, storing secrets, picking a model, and doing a first run. New examples include an SRE agent that investigates production through AWS, a coding agent you mention in Slack that opens pull requests, and a video agent that renders MP4s with Remotion. See Examples.

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More sandbox providers

Tenki, Arker, boxd, and CreateOS join as sandbox providers you can bring your own account for. Each provider now has its own setup and configuration page, plus an overview comparing them. See Sandbox providers.

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Fixes and notes

  • Agents started from Slack before this release can still post in their threads, but new replies there no longer reach them. Mention the bot to start a new agent.
  • On machines you connected yourself, upgrade omnarad to 0.1.36 or later to use Git credentials from the GitHub integration.
  • Self-hosted deployments need OMNARA_MEMORY_DIR on a filesystem shared by the API and every worker. See Memory storage.
  • Blaxel machines that take longer to start from a cold image no longer fail.
  • web_fetch keeps code blocks from fetched pages.
  • The X, Reddit, LinkedIn, and PostHog examples no longer include demo.ts scripts, and posthog-pulse-agent is now posthog-analytics-agent.
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GPT-6, Claude Opus 5.5, and more tools on hosted machines

The hosted catalog now includes GPT-6 Sol and Luna and Claude Opus 5.5, and machines in Omnara-managed pools come with common development tools preinstalled. Also new: Freestyle as a sandbox provider, easier skill creation, image viewing for agents, and a reasoning effort selector.

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New models

omnara-openrouter now includes GPT-6 Sol, GPT-6 Luna, and Claude Opus 5.5, and new agents default to openai/gpt-6-sol. GPT-5.6 Sol, GPT-5.6 Luna, and Claude Opus 5 are being retired: agents already using them keep working, and each model is removed once nothing references it. Update saved configs and scripts that name them.

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More tools on Omnara-managed machines

New machines in Omnara-managed pools, including default-pool, now run Ubuntu 24.04 with common development tools preinstalled: Python, Node.js, Go, uv, pnpm, PostgreSQL, Redis, gh, Python data and document libraries, and Playwright with headless Chromium. Agents can start working without installing them first. Existing machines keep their current image. See Default machine environment.

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Freestyle sandboxes

Bring your Freestyle account as a sandbox provider alongside Blaxel, Unikraft Cloud, Daytona, and Modal. See Machine pools.

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Create skills faster

Drop a folder, archive, or SKILL.md into the Create skill dialog, or write one in the built-in editor. Upload several skills at once and review which are new, which are updated, and which are skipped before anything uploads. Skill uploads from the SDK, CLI, and API now validate correctly. See Skills.

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Agents can see images

read_file returns PNG, JPEG, GIF, and WebP files to the model as images, so agents can look at screenshots and charts they save from a sandbox. See Built-in tools.

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Reasoning effort and account controls

Pick a reasoning effort next to the model in the agent builder for models that support it. You can also delete your account or an organization from the dashboard.

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Fixes

  • MCP errors now return useful status codes instead of generic server errors.
  • The example agents work with the current SDK.
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Agents can now send events to your webhooks

Agents can POST their events to your own endpoint as they work. Also new: a redesigned org overview, per-call machine sizing, and custom headers for model providers.

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Event webhooks

Add event_webhook to an agent’s config with an HTTPS URL and the event types you want, such as tool-call updates or model output. Omnara sends each event as it happens and retries failed deliveries for up to ten minutes. Sign requests with a secret to verify they came from Omnara, and validate payloads with the SDK’s schema. See Event webhook and Webhook payloads.

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Org overview

The organization home page now shows today’s activity and a 30-day summary of model usage, along with your recent agents and profiles.

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Size machines per call

When an agent creates a machine, it can request CPU and memory for that machine, where the provider supports it, within your pool and project limits. The requested size appears in the approval prompt. Agents now find pools through list_machines and select them by ID, so renaming a pool can’t redirect a request.

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Custom headers for model providers

Model providers your organization manages can send extra headers with every request, either as plain values or from secrets. This is useful for API gateways and proxies that need their own authentication or routing headers. See Model providers.

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Fixes and notes

  • Deleting a secret that an agent’s environment references no longer stops new processes or machines from starting; the variable is left out instead. Provider headers that reference a deleted secret are left out the same way.
  • The compiled config now appears under the YAML editor for agents, profiles, and subagents, showing the tools Omnara adds automatically.
  • Archiving a subagent no longer sends a message to its parent.
  • Browser translation extensions no longer crash the dashboard.
  • Self-hosted Docker Compose deployments now bundle RustFS instead of MinIO for artifact storage. See Configuration.
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Agents can now delegate to subagents

Declare subagents in a config and an agent can spin up helpers, hand each one a task, and collect their results in a single conversation. Also new: deferred tool loading, usage and cost pages, large tool results as files, and custom model endpoints in the dashboard.

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Subagents

Add a subagents block to an agent’s config and it gains tools to spawn helpers, send them messages, read their progress, and stop them. A subagent launches from another profile or from a copy of the parent’s own config, starts with a clean context, and shares the parent’s machines. Its final answer arrives back in the parent’s conversation. You set how many can run at once and how deep they can nest, and they appear in the dashboard and API as agents with a parent. See Subagents.Mark any tool deferred: true to keep its definition out of the model’s context until it’s needed. The model calls tool_search to load matching tools on demand, which keeps prompts small and the provider’s prompt cache intact for agents with large MCP tool sets. See Deferred tools.

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Usage and cost

New usage pages for your organization, projects, profiles, and agents show model API usage, and the model catalog now lists pricing per million input and output tokens.

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Large results become files

Tool results over 50 KiB are saved as files instead of filling the conversation. The agent gets a preview and can page through or search the full result with the new read_file and search_files tools, with no machine required. The transfer tools are now upload_file and download_file and work with paths under /artifacts; existing configs were migrated automatically. See Built-in tools.

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Dashboard

Add a model provider with a custom base URL and API format (OpenAI Responses, OpenAI Chat Completions, or Anthropic Messages) from the Add provider dialog, for proxies and self-hosted servers such as LiteLLM, vLLM, or Ollama. Open an agent’s raw event log from its conversation, and get a warning before leaving unsaved agent or profile edits.

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Reliability and API notes

Daemon crashes on connected machines now back off instead of restarting in a tight loop, and failure reports capture the crash output. Dependency updates resolved all open high-severity advisories. For API users: machine tools and bindings now use public machine IDs (mch_...) and the per-agent machine_ref field was removed from responses.
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Omnara is now available over MCP

MCP joins the API, SDK, and CLI as a way to work with Omnara. Connect Claude Code, Cursor, or any MCP client to the Omnara API and spin up Omnara agents from another agent. Also new: Modal sandboxes, Amazon Bedrock with AWS credentials, and in-place secret editing.

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Connect an MCP client

Add https://app.omnara.com/mcp to any MCP client. For example, with Claude Code:
Claude Code
Or with Codex:
Codex
Sign in through the browser on first use; there are no tokens to paste. Your agent can then launch Omnara agents, send them messages, follow their progress, and manage profiles, secrets, and machines, with the same permissions you have in the dashboard. Omnara is also listed in the official MCP Registry as com.omnara/omnara. See Connecting MCP clients.Bring your Modal account as a sandbox provider alongside Blaxel, Unikraft Cloud, and Daytona. Create a pool with your Modal token and choose the image, region, and resource limits. See Machine pools.

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Amazon Bedrock with AWS credentials

Bedrock model providers can authenticate with AWS credentials instead of an API key, including assuming a role. They use the same AWS credential secrets as SigV4 MCP servers. See Model providers.

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Edit secrets in place

Rename a secret or replace its value from the dashboard. Agent configs that reference it keep working. See Secrets.

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Reliability

Agents that reach a model’s output limit now continue their answer instead of stopping short. You can set idle and total timeouts for provider requests. Commands waiting on a machine that looks online but isn’t responding are released after five minutes so the agent can move on.
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Introducing Omnara

On September 2, we relaunched Omnara as the open-source alternative to Claude Managed Agents. Run agents for yourself or your team, or build them into your product through the API. Omnara handles durable execution, sandboxes, and conversation history while you choose how each agent works. Here’s what we’ve shipped so far.

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Agents that pick up where they left off

Agents keep their conversation history across crashes, restarts, and machine disconnects, so work can resume without starting a new conversation. Set one up in the dashboard or with a small configuration file. Save that setup as a profile to reuse it whenever you need a new agent.

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Choose your models and machines

Use models from OpenAI, Anthropic, OpenRouter, or Amazon Bedrock, or connect a compatible model you host yourself. You can choose the model that fits each agent’s work.When an agent needs to run commands, it can use an Omnara-managed sandbox or a machine you connect, such as a laptop or server. You can also bring your own Blaxel, Unikraft Cloud, or Daytona account. Agents can create sandboxes when they need them and release them when the work is done.

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Connect tools and share skills

Agents can search the web, run commands, and work with files using built-in tools. Connect MCP servers to give them access to your services and data, or add custom tools for actions in your own application. You can browse available MCP servers and their tools in the dashboard.Skills let you package instructions and supporting files for work your agents do regularly. Upload and edit them in the dashboard, then reuse them across agents and projects.

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Work with agents as they run

Follow an agent’s progress live, send a correction while it’s working, or queue up its next task. You can decide which actions need approval, and agents can pause to ask questions when they need your input.You can also attach images and documents to a conversation. Agents can return reports, spreadsheets, and other files for you to view or download.

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Slack and scheduled work

Connect an agent profile to Slack so your team can work with it in threads and DMs. Each conversation keeps its own history, and people can answer questions, approve actions, and receive files directly in Slack.For recurring work, schedules can start a new agent or send a task to an existing one. We’ve included examples that collect updates from X, Reddit, LinkedIn, and PostHog and deliver a digest to Slack.

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Build agents into your product

The REST API, TypeScript SDK, and CLI let you launch agents, send messages, follow their progress, and respond to requests for input. You can build these interactions into your own application or work with agents from your terminal.For teams, projects and roles control who can manage or use agents and shared resources. Store credentials as secrets and choose which projects can access your models, machines, and skills.Get started on Omnara Cloud or self-host on your own infrastructure. Omnara is open source under Apache 2.0. The quickstart walks through launching your first agent.