harbor MCP Server
av/harbor
Stop configuring your AI stack. Start using it. One command brings a complete pre-wired LLM stack with hundreds of services to explore.
claude mcp add agentrank -- npx -y agentrank-mcp-server Overview
av/harbor is a Python tool licensed under Apache-2.0. Stop configuring your AI stack. Start using it. One command brings a complete pre-wired LLM stack with hundreds of services to explore. Topics: cli, docker, docker-compose, llm, tools, ai, self-hosted, tool, bash, container, local, npm, package, pypi, safetensors, mcp, automation, homelab, server.
Ranked #508 out of 24840 indexed tools.
In the top 3% of all indexed tools.
Has 3,225 GitHub stars.
Has 22 contributors.
Actively maintained with commits in the last week.
Ecosystem
Score Breakdown
3,225 stars → well-known project
Last commit today → actively maintained
131/221 issues closed → decent issue management
22 contributors → active community
No dependents → no downstream usage
1,075,427 weekly installs → widely installed
Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →
Badge all embed codes →
[](https://agentrank-ai.com/tool/av--harbor/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) <a href="https://agentrank-ai.com/tool/av--harbor/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge"><img src="https://agentrank-ai.com/api/badge/tool/av--harbor" alt="AgentRank"></a> Matched Queries
From the README
https://github.com/user-attachments/assets/e4897391-c5a8-4391-93c3-9f8b76155f11 Setup your local LLM stack effortlessly. ```bash # Starts fully configured Open WebUI and llama.cpp harbor up # Now, Open WebUI can do Web RAG and TTS/STT harbor up searxng speaches ``` Harbor is a CLI and companion app that lets you spin up a complete local LLM stack—backends like Ollama, llama.cpp, or vLLM, frontends like Open WebUI, plus supporting services like SearXNG for web search, Speaches for voice chat, and ComfyUI for image generation—all pre-wired to work together with a single `harbor up` command. No manual setup: just pick the services you want and Harbor handles the Docker Compose orchestration, configuration, and cross-service connectivity so you can focus on actually using your models. ## News - **v0.5.13** - `harbor models pull` no longer reports success when a model download actually failed, and the PrismML backend documents its two Bonsai 2 quants with measured speed and accuracy -Read full README on GitHub →
Get the weekly AgentRank digest
Top movers, new tools, ecosystem insights — straight to your inbox.