Omnara

com.omnara由 omnara.com 發布官方發布者v0.1.0更新於 Oct 24, 2026

Deploy durable AI agents with Omnara, an open-source managed-agent platform.

已驗證Streamable HTTP可網頁執行雲端與基礎設施開發者工具AI 與機器學習

概覽

AI 產生的概覽

Omnara 的託管 MCP 伺服器讓助理在 Omnara Cloud 上啟動與管理具持久狀態的 AI 代理,涵蓋模型、機器、工具與審批。

可以做什麼
  • 在 MCP 用戶端中啟動與管理 Omnara 代理,包括建立新代理並向其傳送訊息
  • 檢視執行中的代理及其事件串流、工具呼叫與審批請求
  • 操作與 CLI 相同的平台物件:設定檔、機器、模型供應商、密鑰、技能與排程觸發器
  • 讓代理在任意相容模型上執行,並使用沙箱或自有機器的算力,依工具設定權限
適用情境
當你希望編碼助理或聊天用戶端不必離開對話就能啟動、監控與引導 Omnara 代理時使用,例如把需要機器、排程或 Slack、GitHub 觸發的長時間任務交給它。它適合已在或正在評估 Omnara 的團隊,而非一次性的本機自動化。
執行需求
遠端端點 app.omnara.com/mcp,使用 streamable HTTP;必須透過瀏覽器完成 OAuth 登入,無需貼上權杖。需要 Omnara 帳號與專案,用戶端須支援 MCP 的 OAuth。使用 Omnara Cloud 可能消耗付費模型或沙箱。
安裝前請注意
此伺服器可啟動在已連線機器或沙箱上執行 shell 指令、編輯檔案的代理,應限定共享的機器與專案範圍。代理可在 Slack、Discord 與 GitHub 上操作,包括留言與提交拉取請求審查。模型、機器與 MCP 憑證儲存在 Omnara 中並依專案共享,使用前請檢查角色權限與工具權限設定。雲端使用可能產生模型與沙箱的按量費用。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Omnara,將其新增到工作區。
  2. 連接 所需的 憑證。它們會被私密儲存,絕不會在公開頁面上展示。
  3. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/com.omnara%2Fomnara/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。 客戶端會在首次連接時完成 OAuth 登入。

{
  "mcpServers": {
    "omnara": {
      "type": "http",
      "url": "https://app.omnara.com/mcp"
    }
  }
}

README

[Omnara] [Omnara]

The open-source managed agent platform

A self-hostable alternative to Claude Managed Agents and OpenAI's Agents API.

[License: Apache 2.0] [npm: @omnara/sdk] [Discord]

Website · Quickstart · Docs · API · Changelog · Discord

Omnara is an open-source managed agent platform. Use the API to run AI agents on any model and any machine, with tools, secrets, permissions, and streaming built in. Self-host it for free under Apache 2.0, or use Omnara Cloud.

Quickstart

Omnara Cloud

Sign in at app.omnara.com. Your first project comes with a model provider (omnara-openrouter) and a pool of managed sandboxes (default-pool), so this config runs as is. Save it as agent.yaml:

yaml
version: v1instruction: |  You are an engineering assistant. Use your machine to run commands.model:  provider_config: omnara-openrouter  name: anthropic/claude-fable-5.1machine_sources:  - machine_pool_name: default-pool

Launch it with the CLI (Node.js 22 or newer). If you're not logged in, the first command opens your browser to sign in.

sh
npx omnara agents launch --file agent.yaml \  --name "Machine assistant" \  --message "Report this machine's operating system and free disk space."

Chat with the agent in your terminal with npx omnara agents chat <agent-id>, or open it in the dashboard to watch its tool calls and reply.

Launch it from your code with the TypeScript SDK

Create an API key in the dashboard and export it as OMNARA_TOKEN, install the SDK with npm install @omnara/sdk, and use the org and project IDs that npx omnara config prints:

ts
import { readFile } from 'node:fs/promises'import { bearerToken, createOmnaraClient, openAgentEventStream, sdk } from '@omnara/sdk'
const client = createOmnaraClient({ auth: bearerToken(process.env.OMNARA_TOKEN!) })const path = { orgID: 'org_...', projectID: 'proj_...' }
const config = await sdk.createAgentConfig({  client,  path,  body: { source: await readFile('agent.yaml', 'utf8'), source_format: 'yaml' },})const launched = await sdk.createAgent({  client,  path,  body: { config: config.data.id, message: "Report this machine's free disk space." },})
const agentID = launched.data.agent.idfor await (const event of openAgentEventStream({ client, path: { ...path, agentID } })) {  console.log(event)}

The quickstart shows the same flow with the REST API.

To have your coding agent do the setup, give it this prompt:

text
Help me set up Omnara by following https://www.omnara.com/SKILL.md

Self-host

Requires Docker with Compose.

sh
git clone https://github.com/omnara-ai/omnara.gitcd omnaradocker compose -f compose.yaml --profile app up -d

Open http://localhost:8000 and sign up. Local development prints the verification link in docker compose logs api, so no email provider is needed. To build from source instead of using published images, run docker compose --profile app up -d --build.

A new instance has no models or machines yet. In the console, add a model provider and a model, connect this computer under Machines, and share both with your project. Sandboxes also work once your instance has a public URL.

Point the CLI at your instance and log in:

sh
npx omnara config --api-url http://localhost:8000/api/v1 --issuer-url http://localhost:8000npx omnara login

In agent.yaml, use your provider and model names, and replace the machine_pool_name entry with machine_name: <your machine>. Then launch it with the same command as above.

The local defaults are intentionally insecure. For a real deployment, follow the self-hosting guide and the configuration reference.

How it works

Your product talks to Omnara, and Omnara runs each agent with the model, tools, and machines in its config.

mermaid
flowchart TB    subgraph yours["Your side"]        users(["Your users"]) --> app["Your app<br/>REST API · TypeScript SDK"]        team["Your team<br/>CLI · dashboard<br/>Slack · Discord · GitHub"]    end    subgraph omnara["Omnara"]        api["API<br/>launch · input<br/>event stream · approvals"] <--> pg[("Postgres<br/>each agent's event log")] <--> worker["Workers<br/>run the agent loop"]    end    subgraph plug[" "]        models["Models<br/>OpenAI · Anthropic<br/>OpenRouter · self-hosted"]        tools["Tools<br/>built-in · skills<br/>MCP · custom"]        machines["Machines<br/>sandboxes or your own<br/>laptop, VM, container"]    end    app --> api    team --> api    worker --> models    worker --> tools    worker --> machines
    classDef side fill:none,stroke:#8b949e,stroke-width:1px    classDef core fill:#506FCF,stroke:#3D5BB5,stroke-width:1px,color:#ffffff    classDef store fill:#3D5BB5,stroke:#2E4794,stroke-width:1px,color:#ffffff    classDef plugin fill:none,stroke:#85A0E6,stroke-width:1.5px    class users,app,team side    class api,worker core    class pg store    class models,tools,machines plugin    style yours fill:none,stroke:#8b949e,stroke-dasharray:4 3    style omnara fill:#506FCF14,stroke:#506FCF,stroke-width:1.5px    style plug fill:none,stroke:#85A0E6,stroke-dasharray:4 3    linkStyle default stroke:#8b949e,stroke-width:1.5px
  • API. Your app, the CLI, and the dashboard all use the same REST API to launch agents, send messages, and answer approvals. Events stream back as they happen.
  • Postgres. Every step of every agent is saved here. That record is the agent's state, so any worker can pick an agent back up after a crash or restart.
  • Workers. Stateless processes that build the model context, call the model, and run tools. An agent only uses a worker while it's taking a turn, so one worker can serve many agents. Add workers to handle more turns at once.
  • Machines. Each machine runs the omnarad daemon, which connects out to Omnara, so agents can run commands there without any inbound ports.

Omnara also uses Redis, blob storage for attachments and tool outputs, and a memory filesystem. The architecture docs cover the details.

Features

Build agents

  • Any model. Bring your own keys for OpenAI, Anthropic, OpenRouter, Amazon Bedrock, LiteLLM, Ollama, or any compatible endpoint, including models you host yourself.
  • Tools. Built-in tools for shell commands, files, web search and fetch, and asking a person a question, plus MCP servers and custom tools that run in your own systems.
  • Skills. Package instructions and files once, attach them to any agent, and the agent loads them when it needs them.
  • Memory. Memory stores give agents files that persist between conversations and can be shared with other agents, with read or read-write access per agent.
  • Subagents. An agent can start subagents with a fresh context, check their progress, and send them new instructions. Each subagent is a full agent you can inspect.

Run them anywhere

  • Machines. Machines are tools the agent uses. Install the Omnara daemon on any macOS or Linux laptop, VM, or container and your agents can run commands and edit files there, with no inbound ports or SSH keys. Or use sandboxes from twelve providers (Agent37, Arker, Blaxel, boxd, CreateOS, Daytona, E2B, Freestyle, Modal, Superserve, Tenki, Unikraft). An agent can use several machines at once (for example, a set of GPU servers) and move between them. If your laptop goes offline, the agent can continue in a sandbox and sync its work back with git.
  • Durable state. Every step is saved, so agents pick up where they left off after crashes, restarts, and machine disconnects.
  • Schedules. Cron triggers with time zones can message an existing agent, launch a new one from a profile, or start a new Slack or Discord thread.

Connect them

  • Slack, Discord, and GitHub. Mention the bot in Slack or Discord to start an agent in a thread, where it replies, asks questions, and requests approvals. On GitHub, an agent can start when a pull request opens or someone mentions it, then read the diff, comment, and submit reviews. To connect another service, build a custom integration on the same public API.
  • Streaming and webhooks. Stream every event as it happens or receive it as a webhook, and send new messages while the agent works.
  • Permissions. Each tool can run immediately, ask a person first, or be blocked. The platform enforces the setting, and the agent waits until someone approves or denies the call.
  • API, SDK, and CLI. A REST API defined in api/openapi/openapi.yaml, a TypeScript SDK (@omnara/sdk), a CLI (omnara), and an MCP server.

Control them

  • Role-based access control and secrets. Organization and project roles for users and API keys. Credentials for models, machines, and MCP servers are stored once and shared with each project explicitly.
  • Multi-tenant. One deployment serves many organizations, each with its own members, projects, secrets, model providers, and machines. Self-hosted operators can give every new organization default models and sandboxes, as Omnara Cloud does.
  • Your data. Self-hosted deployments keep every agent's history in your own Postgres, where you can query it for analytics, evals, and training datasets.

Omnara vs Claude Managed Agents and OpenAI's Agents API

Claude Managed Agents and OpenAI's Agents API are hosted services for running agents on one company's models. Omnara does the same job as an open-source platform you can run anywhere, with any model.

OmnaraClaude Managed AgentsOpenAI's Agents API
SourceOpen source (Apache 2.0)ClosedOpen-source harness (Codex). The hosted service is OpenAI's.
ModelsAny compatible modelClaudeOpenAI
Agent loopOmnara's, works with any modelAnthropic's, built for ClaudeCodex, run and updated by OpenAI
Where the platform runsOmnara Cloud, or your own infrastructureAnthropic's cloudOpenAI's cloud
Where agents runSandboxes from many providers, or your own machinesAnthropic sandboxes, or your own sandboxesOpenAI sandboxes, partner sandboxes, or your own machines
OperationsManaged on Omnara Cloud. You operate it when self-hosting.Managed by Anthropic. You run the sandbox side if you self-host sandboxes.Managed by OpenAI. You run the environment if you bring your own.
Agent historyStored by Omnara on Omnara Cloud and queryable through the API. In your own Postgres when self-hosted.Stored by Anthropic, readable and deletable through the API. Not currently eligible for Zero Data Retention or HIPAA BAA coverage.Stored by OpenAI. No Zero Data Retention support. US data residency only.
PricingFree to self-host. On Omnara Cloud, free with your own keys and machines, or pay as you go for our models and sandboxes.Claude token rates plus $0.08 per active session-hourOpenAI model rates, plus standard rates for OpenAI tools and hosted sandboxes

Choose Claude Managed Agents or the Agents API if you use one company's models and want that company to run everything for you. Choose Omnara if you want to pick your models and machines, run the platform yourself, or keep agent data in your own database.

Where Omnara fits

If you useIt's good forOmnara adds
Workflow builders, such as n8n or ZapierPredictable, step-by-step automationsOpen-ended agents that run code on machines and keep state for days
Agent frameworks, such as Mastra, LangChain, or the OpenAI Agents SDKAgent logic in your app's codeHosting, state, machines, permissions, and integrations, with agents created and changed through an API instead of a redeploy
Agent harnesses, such as Claude Code, the Claude Agent SDK, Codex, OpenCode, or PiOne agent loop in a terminal or on one machineCloud agents that run as a service, across machines and users, started from your app, Slack, GitHub, or a schedule
Managed agent platforms, such as Claude Managed Agents or the Agents APIHosted agents on one company's modelsThe same model of hosted agents, open source, on any model, and self-hostable

Examples

Each of these is an agent.yaml plus a SKILL.md in examples/, and you can deploy any of them with one prompt to your coding agent.

  • Slack coding agent fixes issues you mention in Slack, Discord, or a GitHub pull request and opens a PR.
  • PR review agent reviews your GitHub pull requests against a checkout of the repository and leaves inline findings.
  • SRE agent investigates production problems such as a 5xx spike.
  • Browser agent works in a real browser on long-running tasks.
  • PostHog analytics agent compares yesterday's product usage with the 7-day average and reports what changed.
  • Reddit, X, and LinkedIn signal agents summarize the last 24 hours of posts about a topic you pick.
  • Video generation agent makes short videos from a brief.

There are also code samples for a CLI chat app built on the TypeScript SDK, custom tools over webhooks, and a SharePoint filesystem mount.

Use Omnara from your coding agent

MCP server. Connect Claude Code, Codex, Cursor, or any MCP client that supports OAuth to https://app.omnara.com/mcp to launch and manage Omnara agents. You sign in through the browser, so there are no tokens to paste. In Claude, add it from the connectors directory. Omnara is also listed in the official MCP Registry as com.omnara/omnara.

sh
claude mcp add --transport http omnara https://app.omnara.com/mcpcodex mcp add omnara --url https://app.omnara.com/mcp

Then sign in with /mcp in Claude Code or codex mcp login omnara in Codex. See Connecting MCP clients.

CLI. omnara manages agents, profiles, machines, model providers, secrets, skills, and cron triggers from your terminal or your coding agent's shell. Run npx omnara --help to start.

Setup skill. skills/setup-omnara-agent, also served at omnara.com/SKILL.md, walks a coding agent through setting up Omnara for your project.

Docs for LLMs. docs.omnara.com/llms.txt.

FAQ

What is Omnara? An open-source managed agent platform for running AI agents on any model and any machine.

How much does it cost? Nothing to self-host. Omnara Cloud has no platform fee. You can bring your own model keys and machines for free, or pay as you go for our models at provider token rates and our sandboxes by active time and retained storage. See pricing.

Can I self-host it? Yes. Run it with Docker Compose locally, then follow the self-hosting guide for production. The API, CLI, SDK, and config format are the same on Omnara Cloud and self-hosted deployments.

Which models work? Any model behind an OpenAI Responses, OpenAI Chat Completions, or Anthropic Messages compatible endpoint, including OpenAI, Anthropic, OpenRouter, Amazon Bedrock, LiteLLM, and Ollama.

Development

Source development requires the Go version declared in go.mod, Node.js 24 or newer with Corepack, ripgrep, and Docker with Compose. Run the fast repository gate with make verify. See CONTRIBUTING.md for the full test suite, generated-code workflows, and pull request expectations.

Community

Discord · GitHub Issues · X · Security

License

Apache License 2.0

來源:README.md,提交 fe6822f

工具

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版本歷史

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  1. v0.1.0最新Sep 16, 2026

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