OpenCode integration guide

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Prerequisites

• A SambaCloud account and API key
• Node.js 18 or later (if installing via npm)

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Installation and setup

1

Install OpenCode

• curl
• npm

curl -fsSL https://opencode.ai/install | bash

npm install -g opencode-ai

2

Open the web UI

opencode web

3

Add a custom provider

Go to Settings > Providers and click to add a new custom provider.

4

Configure SambaNova credentials

Enter the following details:

• URL: https://api.sambanova.ai/v1
• API Key: Your SambaCloud API key
• Model Name: For example, MiniMax-M2.7

Get your API key from the SambaCloud portal.

5

Start using SambaNova models

You can now use SambaNova models in your OpenCode workflows.

  "models": {
    "MiniMax-M2.7": {
      "name": "MiniMax-M2.7"
    },
    "gemma-4-31B-it": {
      "name": "gemma-4-31B-it"
    }
  }

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Additional resources

• OpenCode documentation

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How to use sub-agents in OpenCode with SambaNova

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Prerequisites

• opencode installed: curl -fsSL https://opencode.ai/install | bash
• SambaNova API key exported as SAMBANOVA_API_KEY.
• Anthropic API key exported as ANTHROPIC_API_KEY — used by the frontier planner in Demos 2 & 3. opencode auto-discovers it from the env when set, so no provider block is needed in opencode.json.

  # Required for all demos:
  opencode --version && [ -n "$SAMBANOVA_API_KEY" ] && echo OK

  # Demos 2 & 3 also need a frontier planner key:
  [ -n "$ANTHROPIC_API_KEY" ] && echo "planner key OK"

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Wire up SambaNova

mkdir -p ~/sambanova-opencode-demo && cd ~/sambanova-opencode-demo

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "sambanova": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "SambaNova",
      "options": {
        "baseURL": "https://api.sambanova.ai/v1",
        "apiKey": "{env:SAMBANOVA_API_KEY}"
      },
      "models": {
        "MiniMax-M2.7":   { "name": "MiniMax M2.7" },
        "gemma-4-31B-it":   { "name": "gemma-4-31B-it" }
      }
    }
  },
  "agent": {
    "build": { "model": "sambanova/MiniMax-M2.7" },
    "plan":  { "model": "anthropic/claude-sonnet-4-6" }
  }
}

The @ai-sdk/openai-compatible package talks to SambaNova’s OpenAI-compatible /v1/chat/completions endpoint. {env:…} substitution keeps the key out of the file. The anthropic/claude-sonnet-4-6 planner is auto-discovered from ANTHROPIC_API_KEY — no provider.anthropic block needed. Want a SambaNova-only setup with no frontier dependency? Swap the planner to "sambanova/gemma-4-31B-it".

opencode

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Demo 1 — SambaNova end-to-end

Create a minimalist, pet-friendly “hello world” landing page in this directory. One index.html, one style.css, no JS frameworks. Soft pastel palette, a friendly paw-print emoji, a short tagline (“Hello, friend”), and a single call-to-action button. Keep it under 80 lines of HTML+CSS combined. Open the file when done so I can preview it.

open index.html        # or: python3 -m http.server 8000

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Demo 2 — Frontier plans, SambaNova executes

Read index.html and style.css in this directory. Elaborate a plan describing how to extend this landing page into a “pet adoption finder” demo:

• A gallery of 6 placeholder pet cards (name, species, one-line bio) in CSS grid
• A search input that filters cards by name (vanilla JS, no frameworks)
• A dark-mode toggle that persists in localStorage

Include exact file layout, the JS event handlers needed, and a verification checklist a human can run in the browser. Don’t modify any code yet.

Write the plan into PLAN.md and proceed with the execution of every step. After each step, list which acceptance criteria from the plan are now satisfied. Open index.html at the end so I can verify in the browser.

open index.html

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Demo 3 — MCP-fed planning with live library docs

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Install Context7

export CONTEXT7_API_KEY=ctx7sk-…

{
  "mcp": {
    "context7": {
      "type": "remote",
      "url": "https://mcp.context7.com/mcp",
      "headers": { "CONTEXT7_API_KEY": "{env:CONTEXT7_API_KEY}" }
    }
  }
}

No API key works too (free tier, lower rate limits). Drop the headers block.

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The task

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Step 1 — plan agent fetches current docs and writes the plan

Use the context7 MCP server to look up current docs for the date-fns library — specifically formatDistanceToNow with the addSuffix option, and how to load date-fns in a plain browser page via its UMD CDN build (the dateFns global) vs ESM named imports. Elaborate a plan for “Phase 2: relative date labels” describing how to give each pet card a fixed data-added ISO date and render an “Added X days ago” label from it on load. Use the up-to-date API from Context7 — not what you remember. Quote the exact <script> CDN tag, the global function call, and addSuffix usage verbatim from the docs, and include a verification step.

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Step 2 — build agent executes

Update PLAN.md to include the “Phase 2” part and execute it. After loading, open index.html and confirm each card shows an “Added X days ago” label.

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Step 3 — verify

open index.html

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Why this matters

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Tips

• Tab cycles primary agents. Watch the status bar to confirm which model is active.
• @plan / @build in your prompt lets you hand off without switching the active agent.
• Tell the executor to verify (“open index.html and confirm…”) or it will edit files and stop.
• Per-project opencode.json overrides global config — handy for pinning a SambaNova model on one repo without touching others.

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Common gotchas

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Composing with MCP servers

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References

• opencode docs — opencode.ai/docs
• opencode providers — opencode.ai/docs/providers
• opencode agents — opencode.ai/docs/agents
• SambaNova Cloud — cloud.sambanova.ai
• SambaNova Responses API blog — build faster coding agents
• Context7 MCP — github.com/upstash/context7
• Model Context Protocol — modelcontextprotocol.io