Local LLM Worker runs on your own machine — the client starts it, so there is no endpoint to ping. 225 installs a week from npm. Last commit 8 Oct 2026.
Local LLM does Claude's bulk work: reads logs and files, researches the web, writes test-gated code.
We read the source, 2 d ago · rules ccca72095570
A value the model can set ends up inside a file or shell call. That is not a flaw by itself — for a terminal server it is the job — but it is where things go wrong when it is not.
await fs.writeFile(wtTarget, code);
What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.
child = spawn(cmd, args, { cwd, env, stdio: ['ignore', 'pipe', 'pipe'] });
Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.
That is not a flaw by itself — but it is where things go wrong when it is not the job. We re-read this code on every release. Watch it and you hear from us the day another one appears.
This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.
claude mcp add local-llm-worker -- npx -y local-llm-worker
{
"mcpServers": {
"local-llm-worker": {
"args": [
"-y",
"local-llm-worker"
],
"command": "npx"
}
}
}
[mcp_servers.local-llm-worker]
command = "npx"
args = ["-y", "local-llm-worker"]
{
"mcpServers": {
"local-llm-worker": {
"args": [
"-y",
"local-llm-worker"
],
"command": "npx"
}
}
}
{
"mcpServers": {
"local-llm-worker": {
"args": [
"-y",
"local-llm-worker"
],
"command": "npx"
}
}
}
This one needs environment variables set before it will start:
LLW_BASE_URL (Model server URL (Ollama, llama.cpp, LM Studio, vLLM). Default http://localhost:11434), LLW_MODEL (Model to use; optional if the server has only one), LLW_SEARCH_URL (SearXNG URL for web research (optional)).
The author declared them in the registry entry; get the values from the project itself.
Clean messy CSVs: an LLM picks the steps, tested code does the work. Data untouched by the model.
Finds real dead code and proposes a safe, test-gated branch+PR to remove it.
Grade a site's security headers with fixes and a badge; read logs or code for the defender.
Local-first MCP server that reconstructs architecture, workflows and business rules from your code.
Claude-powered AI tools: research, write, code, analyze, translate, debate, pitch, score, and more.
Free MCP server: index a repo's files into the x402-codesearch Worker's search index.
Self-hosted session relay. Shared threads across Claude Code, Cowork, and Claude.ai.
Search the Claude Code Ultimate Guide and machine-readable references from any MCP client.
Answers built from our own checks of this server.