OpenCode

The OpenCode adapter runs OpenCode as a chat backend, driving it over its local HTTP server (@opencode-ai/sdk). Unlike HTTP provider adapters, this is a harness adapter: OpenCode runs its own agent loop and executes its own tools — shell commands, file reads and edits, search — locally on your server. Each chat() call runs one full harness turn; assistant text and reasoning stream as true token-level deltas, and the harness's tool activity streams back as already-resolved tool-call events your UI can render.

Server-only. The adapter spawns (or attaches to) an opencode serve process, so it only works in a Node.js server environment — never in the browser. Treat it like giving OpenCode a shell on the machine it runs on, and configure permissions accordingly.

Installation#

npm install @tanstack/ai-opencode

The opencode CLI must be installed and its providers authenticated on the host:

npm install -g opencode-ai
opencode auth login

A runnable demo lives at examples/sandbox-web — switch the harness (Claude Code, Codex, OpenCode, Grok Build) and sandbox provider per run, with session resume, the harness tool timeline, permission modes, and tool bridging, wired into a TanStack Start app.

Models#

OpenCode is provider-agnostic: it resolves any provider/model id its configured providers support. Address models as provider/model (the adapter splits on the first /):

import { chat } from "@tanstack/ai";
import { opencodeText } from "@tanstack/ai-opencode";

const stream = chat({
  adapter: opencodeText("anthropic/claude-sonnet-4-5", {
    directory: "/path/to/project",
    permissionMode: "acceptEdits",
  }),
  messages: [{ role: "user", content: "Fix the failing test in utils.test.ts" }],
});

Configuration#

Per-call overrides — sessionId, permissionMode, directory — go through modelOptions.

Permissions#

OpenCode asks for permission before mutating files or running commands. A headless server has no one to answer those prompts, so the adapter applies a policy automatically — it never hangs a turn:

• 'default' — bridged TanStack tools run; anything else that would prompt (edits, shell, web fetch) is rejected.

• 'acceptEdits' — additionally auto-approves file-mutation requests (edit / write / patch).

• 'bypassPermissions' — approves everything. Only use this against a sandbox or scratch directory.

  Provide onPermissionRequest to implement your own policy (e.g. allow-list specific commands).

Stateful Sessions#

OpenCode sessions are stateful — the harness keeps the full working context (files read, commands run, conclusions reached) between turns. The adapter surfaces the session id of every fresh run as a custom stream event named opencode.session-id; thread it back via modelOptions.sessionId to resume. When resuming, only the latest user message is sent — the harness already holds the prior context.

Server endpoint:

import {
  chat,
  chatParamsFromRequest,
  toServerSentEventsResponse,
} from "@tanstack/ai";
import { opencodeText } from "@tanstack/ai-opencode";

export async function POST(request: Request) {
  const params = await chatParamsFromRequest(request);

  // Extra fields the client puts in the connection `body` arrive here.
  const sessionId =
    typeof params.forwardedProps.sessionId === "string"
      ? params.forwardedProps.sessionId
      : undefined;

  const stream = chat({
    adapter: opencodeText("anthropic/claude-sonnet-4-5", {
      directory: "/path/to/project",
      permissionMode: "acceptEdits",
    }),
    messages: params.messages,
    modelOptions: { sessionId },
  });

  return toServerSentEventsResponse(stream);
}

Client (React) — capture the session id from the custom event and send it back on subsequent requests:

import { useState } from "react";
import { useChat } from "@tanstack/ai-react";
import { fetchServerSentEvents } from "@tanstack/ai-client";

function CodingAssistant() {
  const [sessionId, setSessionId] = useState<string | undefined>(undefined);

  const { messages, sendMessage } = useChat({
    connection: fetchServerSentEvents("/api/chat", () => ({
      body: { sessionId },
    })),
    onCustomEvent: (name, value) => {
      if (
        name === "opencode.session-id" &&
        typeof value === "object" &&
        value !== null &&
        "sessionId" in value &&
        typeof value.sessionId === "string"
      ) {
        setSessionId(value.sessionId);
      }
    },
  });

  // ... render messages; harness tool activity (bash, edit, read, ...)
  // arrives as regular tool-call parts with results.
}

Sessions live on the server that ran them, so resuming only works against the same server instance (or a shared baseUrl).

Tools#

Two kinds of tools flow through this adapter:

1. Built-in harness tools are executed by OpenCode itself and stream back as tool-call events with results already attached: bash, edit, write, read, grep, and the agent's running todo plan (surfaced as an opencode.todo custom event). Your code never executes them.

2. Your TanStack tools are bridged into the harness: the adapter starts a short-lived Streamable-HTTP MCP server on 127.0.0.1 for the duration of the turn and registers it with OpenCode. Define tools as usual with toolDefinition().server(); tool-call events come back under the names you registered (OpenCode prefixes MCP tools tanstack_… internally, which the adapter strips).

import { z } from "zod";
import { chat, toolDefinition } from "@tanstack/ai";
import { opencodeText } from "@tanstack/ai-opencode";

const lookupTicket = toolDefinition({
  name: "lookup_ticket",
  description: "Look up an issue ticket by id",
  inputSchema: z.object({ ticketId: z.string() }),
}).server(async ({ ticketId }) => {
  return { ticketId, status: "open", title: "Crash on startup" };
});

const stream = chat({
  adapter: opencodeText("anthropic/claude-sonnet-4-5"),
  messages: [{ role: "user", content: "What's the status of ticket T-123?" }],
  tools: [lookupTicket],
});

Client-side and approval-gated tools are not supported. The harness executes tools inside a live process, which cannot pause across HTTP requests to wait for a browser round-trip or a human approval. Passing a tool without a server execute() implementation — or one marked needsApproval — fails fast with a descriptive error. Run those tools outside the harness with a regular provider adapter.

Structured Output#

structuredOutput() is best-effort: OpenCode's prompt API has no native JSON-schema channel, so the schema is embedded as a prompt instruction in a fresh, one-shot session and the final text is parsed (markdown fences are stripped when present). It works for finalization after a chat, but a plain provider adapter (e.g. @tanstack/ai-openai) is the better choice when structured extraction is the primary job — it's faster, deterministic, and doesn't spawn a harness.

Limitations#

• Server-only (Node). The adapter spawns or attaches to an opencode serve process.
• The harness owns the agent loop. TanStack's agent-loop strategies and per-iteration middleware don't apply inside a harness turn.
• No sampling controls. temperature-style options don't exist here.
• Sessions are server-local. Resume requires hitting the same server instance (or a shared baseUrl).
• Cold starts. Spawning a server per turn adds first-token latency; point the adapter at a long-lived baseUrl to avoid it.