LM Studio Code
An agentic coding panel for your local LM Studio models — a Claude Code / Codex–style chat experience that runs entirely on your machine.
Under the hood it drives the open-source OpenCode agent (Apache/MIT) as a headless server, pointed at LM Studio's OpenAI-compatible endpoint. You get a real agent — file edits, shell tools, permissions, multi-step reasoning — with no cloud model and no API key.
Demo
Why
The official Claude Code and Codex VS Code extensions are not open source, so they can't be adapted to local models. The CLIs behind several agents are open, though — and OpenCode in particular ships a headless server + provider-agnostic model layer that happily talks to LM Studio. This extension wraps that server in a native chat panel.
Features
- Chat panel in the Activity Bar (and "Open in Editor Tab" for parallel conversations)
- Streaming responses with markdown + code rendering
- Reasoning blocks (collapsible "Thinking")
- Agent tools — file reads/edits, shell, search — surfaced as tool cards
- Permission prompts — Allow once / Allow always / Deny, inline
- Model picker populated live from LM Studio (shows loaded ● / unloaded ○ + context size)
- Agent modes —
build (can edit) and plan (read-only)
- Session history — browse, resume, rename-by-first-message, delete
- Auto-context — reloads the selected model with an adequate context window via the
lms CLI so OpenCode's large system prompt doesn't overflow a 4096-token default
Requirements
- VS Code 1.104+
- LM Studio running with its local server started (default
http://127.0.0.1:1234) and at least one chat model
- OpenCode installed (
brew install sst/tap/opencode or npm i -g opencode-ai). Auto-detected from PATH or ~/.opencode/bin/opencode.
- (recommended) the
lms CLI for automatic context-window management
Quick start
- Start LM Studio's server and load a model.
- Install this extension (or run it from source — see below).
- Click the spark icon in the Activity Bar.
- Pick a model, type a task, hit Enter.
Settings
| Setting |
Default |
Description |
lmstudioCode.lmStudioBaseUrl |
http://127.0.0.1:1234/v1 |
LM Studio OpenAI-compatible base URL |
lmstudioCode.opencodePath |
(auto) |
Path to the opencode binary |
lmstudioCode.serverPort |
0 |
Embedded server port (0 = auto) |
lmstudioCode.defaultModel |
(first) |
Default model id |
lmstudioCode.agent |
build |
build or plan |
lmstudioCode.autoEnsureContext |
true |
Reload model with adequate context before prompting |
lmstudioCode.minContextLength |
16384 |
Context length to (re)load with |
lmstudioCode.gpuOffload |
max |
GPU offload for lms load |
How it works
VS Code webview (chat UI)
│ postMessage
▼
Extension host (bridge)
│ HTTP + SSE (raw fetch)
▼
opencode serve ──OpenAI /v1──▶ LM Studio (local model)
(headless, config injected via OPENCODE_CONFIG_CONTENT)
The LM Studio provider is injected into OpenCode at launch via the
OPENCODE_CONFIG_CONTENT environment variable — nothing is written to your
workspace or global config. Discovered LM Studio models are declared in the
provider's models map (OpenCode requires this for custom OpenAI-compatible
providers).
Develop from source
npm install
npm run compile # type-check + bundle (extension + webview)
# then press F5 in VS Code to launch the Extension Development Host
npm run package:vsix # build a .vsix
License
MIT
