Sezzlee Local LLM runs on your own machine — the client starts it, so there is no endpoint to ping. 12 installs a week from npm. Last commit 11 Oct 2026.
Let a planning agent hand bounded language work to a local Ollama model.
Today is the operative word: we check Sezzlee Local LLM every 15 minutes and re-read its code on every release. Watch it and you find out the day that stops being true.
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 llm -- npx -y @sezzlee/llm-mcp
{
"mcpServers": {
"llm": {
"args": [
"-y",
"@sezzlee/llm-mcp"
],
"command": "npx"
}
}
}
[mcp_servers.llm]
command = "npx"
args = ["-y", "@sezzlee/llm-mcp"]
{
"mcpServers": {
"llm": {
"args": [
"-y",
"@sezzlee/llm-mcp"
],
"command": "npx"
}
}
}
{
"mcpServers": {
"llm": {
"args": [
"-y",
"@sezzlee/llm-mcp"
],
"command": "npx"
}
}
}
This one needs environment variables set before it will start:
SEZZLEE_LLM_MODEL (Ollama model to call), SEZZLEE_LLM_BASE_URL (Ollama base URL), SEZZLEE_LLM_NUM_CTX (Context window in tokens), SEZZLEE_LLM_TIMEOUT_MS (Per-call timeout in milliseconds), SEZZLEE_LLM_KEEP_ALIVE (How long Ollama keeps the model loaded), SEZZLEE_LLM_ROOT (Workspace folder paths resolve against), SEZZLEE_LLM_OUTPUT_DIR (Folder local_map writes its CSV into).
The author declared them in the registry entry; get the values from the project itself.
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Answers built from our own checks of this server.