Sezzlee Local LLM MCP Server

by sezzleeio.github.sezzlee/llmv0.1.3

MCP server that lets a planning agent (Codex, Claude Code, Cursor) hand bounded language work to a local Ollama model.

1Node.jsstdioofficial registry

context tax

pending

security

97/100

cold start

pending

freshness

Activetoday

Our reading of Sezzlee Local LLM, from the data

Sezzlee Local LLM is a ai & llm tools MCP server from sezzlee, listed in the official MCP Registry.

We haven't measured its tool list yet, so its token cost is unknown.

Maintenance is active: the last public signal was in the last day (2026-10-18). For comparison, 59% of ai & llm tools servers are active or maintained.

With 1 GitHub stars it ranks #978 of 3,169 ai & llm tools servers we index.

It runs locally on your machine over stdio.

Install Sezzlee Local LLM MCP server

claude mcp add llm-sezzlee -e SEZZLEE_LLM_MODEL='<sezzlee-llm-model>' -- npx -y @sezzlee/llm-mcp

{
  "mcpServers": {
    "llm-sezzlee": {
      "command": "npx",
      "args": [
        "-y",
        "@sezzlee/llm-mcp"
      ],
      "env": {
        "SEZZLEE_LLM_MODEL": "<sezzlee-llm-model>"
      }
    }
  }
}

Add to ~/.cursor/mcp.json (global) or .cursor/mcp.json (project).

{
  "mcpServers": {
    "llm-sezzlee": {
      "command": "npx",
      "args": [
        "-y",
        "@sezzlee/llm-mcp"
      ],
      "env": {
        "SEZZLEE_LLM_MODEL": "<sezzlee-llm-model>"
      }
    }
  }
}

Settings → Developer → Edit Config (claude_desktop_config.json), then restart.

{
  "servers": {
    "llm-sezzlee": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@sezzlee/llm-mcp"
      ],
      "env": {
        "SEZZLEE_LLM_MODEL": "<sezzlee-llm-model>"
      }
    }
  }
}

Add to .vscode/mcp.json in your workspace.

{
  "mcpServers": {
    "llm-sezzlee": {
      "command": "npx",
      "args": [
        "-y",
        "@sezzlee/llm-mcp"
      ],
      "env": {
        "SEZZLEE_LLM_MODEL": "<sezzlee-llm-model>"
      }
    }
  }
}

Add to ~/.codeium/windsurf/mcp_config.json.

Configuration

Variable	Required	Secret	Description
SEZZLEE_LLM_MODEL	yes	—	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

Security signals

97/100 — no known issues found as of 2026-10-19, from the checks below. This is not a guarantee of safety; review what a server can do before connecting it.

Deductions

No security policy (SECURITY.md)-3

Checks

✓Repository hygiene (archived, activity, license, security policy)
○Package metadata (install scripts, provenance) — pending
○Tool descriptions (prompt-injection and hidden-text heuristics) — pending
○Source scan (secrets, CVEs, risky code) by vectra-guard — pending

Scan it yourself before installing with vectra-guard, the open-source agent security CLI. Scoring rules

Freshness

Active — last maintenance signal today. The newest of the signals below sets the band.

Last commit (default branch)
2026-10-18 · today · GitHub
Latest release
no data · GitHub
Package published
no data · npm/PyPI
Registry entry updated
2026-10-11 · 7d ago · official registry · v0.1.3

How it compares in AI & LLM Tools

Against the most-starred ai & llm tools servers we index. Token cost is per model turn, measured from each server's live tool list.

Server	Stars	Tools	Tokens / turn	Freshness	Runs
Sezzlee Local LLM (this)	1	—	not measured	Active	local
Memory	91,356	—	not measured	Active	local
Claude Flow	76,638	—	not measured	Active	local
Next AI Draw.io	36,318	—	not measured	Active	local
Serena Agent	30,371	—	not measured	Active	local
Trycua	30,160	—	not measured	Active	—

All ai & llm tools MCP servers

FAQ

›How do I install the Sezzlee Local LLM MCP server in Claude Code?

Run: claude mcp add llm-sezzlee -e SEZZLEE_LLM_MODEL='<sezzlee-llm-model>' -- npx -y @sezzlee/llm-mcp. For Cursor, VS Code, Claude Desktop and Windsurf, use the install tabs above.

›Does Sezzlee Local LLM require an API key?

Yes. It expects SEZZLEE_LLM_MODEL.

›Can I use Sezzlee Local LLM as a remote (hosted) MCP server?

No hosted endpoint is published; it runs locally over stdio.

›Is Sezzlee Local LLM in the official MCP registry?

Yes, as io.github.sezzlee/llm.

Sources and method

Official MCP Registry entry: updated 2026-10-11
GitHub repository: fetched 2026-10-19
Package registry (npm / PyPI): listed
Security signals, computed by us: 2026-10-19
Last checked against all sources: 2026-10-19

The description, packages and links come from the maintainer's own published metadata. Token cost, security signals, freshness and the reading above are MCPSkillHub's own measurements; see the methodology. Spot an error? Request a correction or claim the listing.