Show HN: Anyclaude-SDK – Claude Code-Style SDK for OpenAI/Anthropic Endpoints

Anyclaude-SDK, a new open-source SDK that brings Claude Code-style agent capabilities to any OpenAI- or Anthropic-compatible LLM endpoint, has been released on npm. The SDK supports multi-agent teams, MCP servers, and runs in the browser via WebContainer, Node, and Bun without requiring a backend or OAuth. It exposes the same interface as the official Anthropic Claude agent SDK, allowing code written for that SDK to work unchanged.

Claude Code agent capabilities — tools, the tool loop, multi-turn conversations, MCP, sub-agents, multi-agent teams , sessions — against any OpenAI- or Anthropic-compatible LLM endpoint , running in the browser WebContainer https://webcontainers.io , Node , and Bun . No backend required, no OAuth, no native binaries. Live demo: a full IDE running in your browser ·Docs: anyclaude-docs.puter.site ·React UI kit: anyclaude-react It exposes the same query async-generator interface and the same SDKMessage envelope as @anthropic-ai/claude-agent-sdk , so code written against the official SDK can iterate our output unchanged. Multi-agent teams go beyond one agent: a coordinator delegates board tasks to worker sub-agents in parallel, you can dispatch a message to a running worker and have it land on its next tool round push delivery, like the message queue , supervise them live with background dispatch, block for the next finished worker with event-driven — integrate each result as it lands, no busy-polling , and even run agents in wait for worker separate Web Workers or browser tabs that share one mailbox via BroadcastChannelMailbox . See Teams & sub-agents https://anyclaude-docs.puter.site/teams.html . npm install anyclaude-sdk @webcontainer/api @webcontainer/api is an optional peer dependency — only needed if you use WebContainerWorkspace . You can supply your own FileSystem / CommandExecutor . js import { WebContainer } from '@webcontainer/api' import { query, WebContainerWorkspace, createOpenAIClient, ALL CLAUDE CODE TOOLS, } from 'anyclaude-sdk' // 1. Boot a WebContainer and wrap it as a workspace. const wc = await WebContainer.boot const workspace = new WebContainerWorkspace wc // 2. Point at any OpenAI-compatible endpoint. const llm = createOpenAIClient { apiKey: import.meta.env.VITE OPENAI API KEY, baseUrl: 'https://api.openai.com/v1', // or Groq, Together, OpenRouter, local… model: 'gpt-4o', } // 3. Run the agent — same shape as the official SDK. for await const msg of query { prompt: 'List the files and summarize the project', workspace, llm } { if msg.type === 'assistant' { for const block of msg.message.content { if block.type === 'text' console.log block.text } } else if msg.type === 'result' && msg.subtype === 'success' { console.log 'Done:', msg.result } } Connect external MCP servers or define in-process tools. Because browsers block direct cross-origin MCP fetches CORS , pass a mcpProxy for remote servers: js import { createSdkMcpServer, tool } from 'anyclaude-sdk' const calc = createSdkMcpServer { name: 'calc', tools: tool 'add', 'Add two numbers', { type: 'object', properties: { a: { type: 'number' }, b: { type: 'number' } }, required: 'a', 'b' }, args = { content: { type: 'text', text: String args.a + args.b } } , } query { prompt, workspace, llm, mcpServers: { calc, // in-process, no network docs: { type: 'http', url: 'https://mcp.example.com' }, // remote }, // Route remote MCP through a CORS proxy function, {url} / {rawUrl} template, or bare prefix : mcpProxy: 'https://my-proxy.example/?url={url}', } Remote tools are exposed as mcp <server <tool . Three transport clients, all implementing the same LLMClient interface: js import { createOpenAIClient, createAnthropicClient, createResponsesClient } from 'anyclaude-sdk' // OpenAI-compatible Chat Completions OpenAI, Groq, Together, OpenRouter, xAI, Kilo, local… const a = createOpenAIClient { apiKey, baseUrl: 'https://api.x.ai/v1', model: 'grok-build-0.1' } // Anthropic Messages API const b = createAnthropicClient { apiKey, model: 'claude-sonnet-4-6' } // OpenAI Responses API POST /v1/responses const c = createResponsesClient { apiKey, model: 'gpt-4o' } // AgentRouter gateway sponsor — one-line preset over createOpenAIClient; key // falls back to AGENTROUTER API KEY. Reaches Claude/GPT/Gemini/DeepSeek/GLM/… via one base URL. import { createAgentRouterClient } from 'anyclaude-sdk' const d = createAgentRouterClient { model: 'claude-sonnet-4-5-20250929' } All three normalize tool calls, streaming, and usage to the same StreamResult , and include a fallback parser for models that emit tool calls as inline text. Every client also accepts extraHeaders / extraBody merge provider-specific headers/params without a custom client and surfaces retries on the result when transient failures were retried. Use a PromptStream to push user turns over time: js import { query, PromptStream } from 'anyclaude-sdk' const prompts = new PromptStream const session = query { prompt: prompts, workspace, llm, model: 'gpt-4o' } prompts.push 'Create a hello.txt with a greeting' // …later, based on UI input: prompts.push 'Now translate it to French' prompts.end // close the conversation for await const msg of session { // render msg… } ALL CLAUDE CODE TOOLS includes: | Tool | Purpose | |---|---| bash | Run shell commands via jsh 2 &1 / /dev/null redirects are stripped | read file | Read text numbered lines, offset/limit , images auto-downsampled base64 , PDFs document block , and notebooks .ipynb cells + outputs ; binary files are rejected with guidance | write file | Write a file, creating parent dirs | edit file | Exact-match string replace requires a prior read | multi edit | Apply a sequence of edits to one file atomically | notebook edit | Replace/insert/delete cells in a .ipynb | delete file | Remove a file/dir | glob | Find files by glob pattern , , ? | grep | Regex search across files | list files | List a directory | todo write | Track a multi-step task list across turns | web fetch | Fetch a URL → clean Markdown via the Jina Reader CORS-free, JS-rendered | web search | Web search via Jina + DuckDuckGo HTML; returns top-N title/URL/snippet | render page | Render a public page in a headless browser: Playwright-style actions click/fill/scroll/press , accessibility snapshot , evaluate JS, console+network logs , and a screenshot as a viewable image or extracted markdown/html. Refuses localhost/private/WebContainer hosts. | read file dispatches by file type. Image and PDF bytes are forwarded to the model automatically as a follow-up user turn Anthropic gets native image / document blocks; OpenAI-compatible endpoints get image url / file parts , so the model can actually see the file, not just a text summary. Tune the caps via limits : query { prompt, workspace, llm, limits: { maxTokens: 25000, maxImageBytes: 3 750 000, maxPdfPages: 20 } } Pass a subset, or your own Tool , via tools: : js import { readFile, writeFile, editFile } from 'anyclaude-sdk' query { prompt, workspace, llm, tools: readFile, writeFile, editFile } A user turn beginning with / is intercepted. Built-ins: /help , /clear , /compact focus summarizes history to free context , /tools , /cost , /model . Define your own prompt-template commands: js import { query, promptCommand } from 'anyclaude-sdk' query { prompt: promptStream, workspace, llm, commands: promptCommand 'review', 'Review the diff', 'Review this code and list issues: $ARGUMENTS' , } // user types: /review src/app.ts Enable with background: true to run sub-agents or long work off the critical path. The task tool gains run in background returns a task id immediately , and task list / task output / task stop tools let the agent poll them. Optional off-main-thread execution via a Comlink worker harness exposeBackgroundWorker / wrapWorker ; the in-thread manager works without it. query { prompt, workspace, llm, agents: {}, background: true } Two halves: Comlink for main→worker control wrapWorker / exposeBackgroundWorker , above , and BroadcastChannelMailbox so agents in different workers gossip mailbox-style. It's a drop-in Mailbox , so the existing team tools send message / dispatch tasks work unchanged across workers: js import { BroadcastChannelMailbox } from 'anyclaude-sdk' // inside each Web Worker / tab / worker thread, same channel name: const mailbox = new BroadcastChannelMailbox { channelName: 'team', origin: 'planner' } query { prompt, workspace, llm, team: true, mailbox } // messages sent by one worker land in the addressed agent's inbox in another. Uses the global BroadcastChannel by default. For durable cross-tab delivery IndexedDB/localStorage fallbacks, older browsers, Node use the one-call helper — it's backed by the bundled broadcast-channel https://www.npmjs.com/package/broadcast-channel package, lazy-imported so it stays out of bundles that don't use it: js const mailbox = await BroadcastChannelMailbox.crossTab { channelName: 'team', origin: 'planner' } query { prompt, workspace, llm, team: true, mailbox } Push delivery to a running agent. Messages addressed to an agent are auto-injected into its transcript at the next turn boundary — same model as the message queue, but from the shared mailbox. So a coordinator or peer, or another worker can redirect a running sub-agent mid-task and it lands on the sub-agent's next tool round, no polling tool needed. dispatch tasks names each worker worker:<taskId so you can target a specific one: mailbox.send 'coordinator', 'worker:task 1', 'while you work: also add logging' // worker:task 1 sees " Team messages - from coordinator: ..." on its next step. On by default with team: true ; opt out via query { deliverTeamMessages: false } . You aren't tied to WebContainer. A Sandbox is just a FileSystem plus a CommandExecutor , and you can mix and match. Adapters wrap each provider's client structurally no hard dependency on their SDKs — install only the one you use : js import { E2BSandbox, VercelSandbox, DaytonaSandbox, CloudflareSandbox } from 'anyclaude-sdk' // e.g. E2B import { Sandbox } from 'e2b' const sbx = await Sandbox.create const workspace = new E2BSandbox sbx query { prompt, workspace, llm } Supported: WebContainer , E2B , Vercel Sandbox , Daytona , Cloudflare Sandbox , and LocalSandbox real OS . All implement the same Sandbox interface. Run the agent directly against the host machine's filesystem and shell — like Claude Code — with automatic platform detection Windows / macOS / Linux : js import { LocalSandbox, createAnthropicClient, query } from 'anyclaude-sdk' const workspace = new LocalSandbox { cwd: '/path/to/project' } // defaults to process.cwd const llm = createAnthropicClient { baseUrl, model: 'claude-sonnet-4-6', apiKey } for await const msg of query { prompt: 'add a CLI flag and run the tests', workspace, llm } { / … / } The agent's working directory is taken from the sandbox automatically. See examples/local-agent.mjs for a runnable headless demo. On Windows it uses cmd.exe ; elsewhere $SHELL / /bin/sh override via shell / shellArgs . For a durable local filesystem in the browser, use a DB-backed FS and seed a standard Linux tree. DexieFileSystem IndexedDB is the recommended default — persistent across reloads, indexed for fast readdir / glob , with metadata mode, mtime, symlinks : js import { DexieFileSystem, OpfsFileSystem, seedLinuxTree, composeWorkspace, NoopCommandExecutor, } from 'anyclaude-sdk' const fs = new DexieFileSystem 'my-project-fs' // or: new OpfsFileSystem await seedLinuxTree fs // /bin /etc /home/user /tmp /usr … // File-only agent no shell : const workspace = composeWorkspace fs, new NoopCommandExecutor , '/home/user' // …or pair a persistent FS with a remote shell: // const workspace = composeWorkspace fs, new E2BSandbox sbx , '/home/user' OpfsFileSystem Origin Private File System is offered alongside Dexie for large-binary / native-handle scenarios; use OpfsFileSystem.isSupported to feature-detect. A MemoryFileSystem also ships for tests: js import { MemoryFileSystem, NoopCommandExecutor, composeWorkspace } from 'anyclaude-sdk' const fs = new MemoryFileSystem await fs.writeFile '/app/index.ts', 'export const x = 1' const workspace = composeWorkspace fs, new NoopCommandExecutor Declare reusable prompt-skills inline — each becomes a /name slash command and is invokable by the agent through the skill tool. $ARGUMENTS is substituted at call time: js import { query, defineSkill } from 'anyclaude-sdk' query { prompt, workspace, llm, skills: defineSkill { name: 'changelog', description: 'Summarize git changes into a changelog entry', instructions: 'Write a concise changelog entry for: $ARGUMENTS', argumentHint: '<since ', } , , } You can also pass plain Skill objects, or skills: true to load .claude/skills/ .md from the workspace. Run query in a serverless function and stream SDKMessage s to the browser. For runs longer than the platform's time cap, checkpoint at a turn boundary and continue transparently in a fresh invocation: // pause near the deadline, persist to the store, emit a paused message query { prompt, workspace, llm, sessionStore, maxDurationMs: 20 000 } // later — resume + continue the tool loop with NO new user message query { workspace, llm, sessionStore, resume: true, continueRun: true } Pluggable SessionStore adapters all implement SessionStoreLike : SessionStore IndexedDB , MemorySessionStore , KVSessionStore Vercel KV / Upstash , RedisSessionStore , PostgresSessionStore Neon / pg / postgres.js , SupabaseSessionStore . Declare tools the host executes — e.g. run bash in the user's browser WebContainer while the agent loop runs on your server. The run pauses with a client tool request ; the client executes it and you resume with the result: js import { WORKSPACE TOOL NAMES } from 'anyclaude-sdk' query { prompt, llm, workspace, sessionId, clientTools: WORKSPACE TOOL NAMES } // → emits client tool request + pauses query { llm, workspace, sessionId, resume: true, continueRun: true, clientToolResults } // → continues On the browser side, anyclaude-react turns those into a ready executor map backed by any workspace — a WebContainer real shell + files , the user's IndexedDB DexieFileSystem , OPFS, or memory: js import { createWebContainerClientTools, createWorkspaceClientTools } from 'anyclaude-react' useAgent { endpoint: '/api/agent', clientTools: createWebContainerClientTools wc } // files + bash useAgent { endpoint: '/api/agent', clientTools: createWorkspaceClientTools new DexieFileSystem 'my-db' } // IndexedDB Provide onAskUser and the agent gains an ask user question tool to put a decision to the user — multiple-choice or free-text inputType: 'choice' | 'text' | 'textarea' | 'number' , plus allowOther . Hosts that only render choices can ignore the new fields: query { prompt, workspace, llm, onAskUser: async { question, options, inputType } = inputType && inputType == 'choice' ? promptText question : pickOne question, options } The agent loop runs server-side, so your system prompt, tool instructions, and retrieved context live in the server→LLM request and never reach the browser . To also strip sensitive artifacts reasoning, raw tool output / RAG, model identity from the streamed messages, wrap the stream — a pure, opt-in output transform: js import { projectMessages } from 'anyclaude-sdk' for await const m of projectMessages query { / ... / } , { preset: 'public' } res.write JSON.stringify m + '\n' paused and client tool request control messages are always preserved. Note: anything that runs in the browser — createAgentClient mode — necessarily exposes its request; use the server/endpoint path when the prompt is proprietary. npm install anyclaude-react useAgent plus restylable components — chat AgentChat , ChatPanel , Transcript , MarkdownMessage , Composer , Working , ToolCall and an IDE set Terminal , FileExplorer , CodeEditor , AskUser . createAgentClient / createEndpointClient auto-stitch paused continuations and run clientTools in the browser. Stand up an Anthropic Messages API-compatible endpoint backed by any OpenAI-compatible model, so Claude Code itself or any Anthropic-Messages client runs against DeepSeek / Qwen / GLM / Kimi / local Ollama. Unlike a naive proxy, inline tool-call dialects are recovered into proper tool use blocks , so tool use actually works on cheap models. js import { createOpenAIClient } from 'anyclaude-sdk/llm' import { anthropicToChat, anthropicSSE } from 'anyclaude-sdk/anthropic-endpoint' const llm = createOpenAIClient { baseUrl: 'https://api.deepseek.com/v1', model: 'deepseek-chat', apiKey } // POST /v1/messages: for await const evt of anthropicSSE llm, anthropicToChat body , { model: 'deepseek-chat' } res.write evt // then: ANTHROPIC BASE URL=http://localhost:8787 claude Runnable: examples/claude-code-router /pipilot-dev/anyclaude-sdk/blob/main/examples/claude-code-router . Frontier models emit clean native function-calls; cheaper ones often don't. Three layers in anyclaude-sdk/llm close the gap: tool-call dialects parseToolCalls — xml-function / hermes / json-fence , auto-detected model profiles profileForModel — qwen/deepseek/moonshot/zhipu/mistral/llama , and self-healing argument repair query { repairToolCalls } , on by default — validates args and feeds the model a corrective tool result instead of running with garbage . Prove it on your endpoints with scripts/compat-matrix.mjs /pipilot-dev/anyclaude-sdk/blob/main/scripts/compat-matrix.mjs → COMPATIBILITY.md /pipilot-dev/anyclaude-sdk/blob/main/COMPATIBILITY.md . npm create anyclaude-app@latest my-app template: bolt — WebContainer + chat + live preview, no backend The bolt template wires useWebContainerPreview { wc } boot a dev server → live preview URL + a browser-side query + the IDE components. See anyclaude-react react-ui-kit--anyclaude-react . Keep a large pool of rarely-used tools out of the per-turn payload big savings on weak/uncached models while staying discoverable + callable. Mark them deferred; tool search indexes them and the loop arms a tool sends its schema on subsequent turns once search surfaces it — then it executes normally. query { prompt, workspace, llm, extraTools: deploy, ...integrationTools , // e.g. 35 integration tools deferredTools: 'stripe charge', 'supabase query', / … the niche ones / , } // or per-tool: defineTool { name, description, parameters, run, defer: true } Only the lean core + tool search are sent each turn; the model searches when it needs a niche tool, the SDK arms it, and the call goes through. Register 35, send ~10. Opt-in knobs for token cost and latency — especially on weak / uncached models: query { prompt, workspace, llm, systemPromptPreset: 'lean', // ~70% shorter built-in prompt — saved every turn on uncached models keepToolResults: 6, // context editing: stub tool results older than the last 6 caps transcript growth parallelToolExecution: true, // run a turn's read-only tool calls concurrently ~2× faster on multi-read turns deferredTools: / niche tools / , // keep rarely-used tools out of the payload until tool search arms them } // custom read tool opting into parallelism: defineTool { name: 'get logs', description: '…', parameters, run, parallelSafe: true } Mutating tools / bash / delegated client tools always execute serially; keepToolResults and parallelToolExecution preserve correctness, just trim cost/latency. Live compaction marker — autoCompact emits a compact boundary with status: 'start' before summarizing for a live "compacting…" shimmer and status: 'end' after with post tokens . Cancel a queued message — MessageQueue.push returns a stable id; remove id cancels a single pending message per-pill ✕ in a UI . BYO LLM client — reuse the SDK's wire codec: toOpenAIMessages , consumeSSE , and the LLM types from anyclaude-sdk/llm no bare-root import in browser bundles . Runnable Vite projects in examples/ /pipilot-dev/anyclaude-sdk/blob/main/examples : WebContainer IDE — real shell + Node in the tab , browser-ide browser-chat , claude-code-router , vercel-kv-survivor , vercel-supabase-survivor , vercel-indexeddb-survivor , server brain / browser hands . Try the vercel-clienttools . live demo https://anyclaude-docs.puter.site/demo/ query options : AsyncGenerator<SDKMessage — main entry. prompt: string | AsyncIterable<SDKUserMessage workspace: FileSystem & CommandExecutor llm: LLMClient tools? , extraTools? , allowedTools? / disallowedTools? , deferredTools? lazy-load , model? , systemPrompt? / appendSystemPrompt? , maxTurns? default 50 , cwd? , abortController? - serverless: sessionStore? , resume? , maxDurationMs? , continueRun? - client tools: clientTools? , clientToolResults? ; interactive: onAskUser? - also: mcpServers? , agents? , commands? , hooks? , background? , team? , memory? , permissionMode? / canUseTool? , messageQueue? createOpenAIClient / createAnthropicClient / createResponsesClient WebContainerWorkspace , MemoryFileSystem , NoopCommandExecutor , LocalSandbox , composeWorkspace defineTool custom tools , projectMessages server-side stream redaction ALL CLAUDE CODE TOOLS , individual tools, toolDefs , toolByName - browser-clean subpaths: anyclaude-sdk/{query,loop,llm,fs,workspace,tools,session,memory,compact,permissions,skills,queue,prompt,anthropic-endpoint,telemetry} anyclaude-sdk/llm : parseToolCalls + dialects, profileForModel model profiles , validateToolArguments repair , toOpenAIMessages / consumeSSE BYO-client codec anyclaude-sdk/anthropic-endpoint : anthropicToChat , anthropicSSE , streamResultToAnthropicMessage Claude-Code router runToolLoop /loop , compactWithWindow /compact , track / telemetryEnabled /telemetry - All SDK message types, ContentBlockParam , LLMClient , ToolDef , SessionStoreLike , etc. | Feature | Official SDK | anyclaude-sdk | |---|---|---| | Auth | OAuth token | None required | | Backend | claude.ai API | Any OpenAI/Anthropic endpoint | | Runtime | Node only | Browser, Node, Bun | | File ops | Native filesystem | Pluggable WebContainer / Memory / IndexedDB / local | | Commands | Native shell | jsh WebContainer / local / client-side tools | | MCP / slash commands / background tasks / sub-agents | Built-in | Built-in | | Serverless survivor + prompt projection | — | Built-in | The SDK emits anonymous, opt-out usage telemetry SDK version, runtime, a coarse model-family bucket, and which features are used — never code, prompts, repo identity, paths, or keys. It sends to an aggregate-only collector a Puter Worker; source in examples/telemetry-collector /pipilot-dev/anyclaude-sdk/blob/main/examples/telemetry-collector . Disable with ANYCLAUDE TELEMETRY=0 , DO NOT TRACK=1 , or query { disableTelemetry: true } ; repoint with ANYCLAUDE TELEMETRY URL or set it to '' to send nowhere . Full disclosure: TELEMETRY.md /pipilot-dev/anyclaude-sdk/blob/main/TELEMETRY.md . MIT