{"id":"vllm-mcp-server","name":"vllm-mcp-server","af_score":56.5,"security_score":44.5,"reliability_score":30.0,"what_it_does":"vLLM MCP server that exposes vLLM chat/completions plus model and status/metrics capabilities to MCP-compatible clients. It can also start/stop/manage a vLLM instance in Docker/Podman with platform/GPU-aware container selection and runtime configuration via environment variables and MCP tools.","best_when":"You want local, self-hosted LLM inference accessible via MCP tools, and you are comfortable running containers (Docker/Podman) on your machine with configured environment variables (e.g., HuggingFace token).","avoid_when":"You need strong tenancy isolation, robust operational security controls for container execution, or you cannot tolerate managing/gating access to local inference endpoints and container lifecycle.","last_evaluated":"2026-04-04T21:40:04.300536+00:00","has_mcp":true,"has_api":false,"auth_methods":["Environment variable pass-through for HuggingFace token (VLLM_HF_TOKEN)","Optional vLLM API key via environment variable (VLLM_API_KEY) if required by the upstream vLLM server"],"has_free_tier":false,"known_gotchas":["MCP client tooling must be configured correctly (command/args/env) for the MCP server process to start","HuggingFace gated models require VLLM_HF_TOKEN; failures may occur if unset/invalid","Container runtime and GPU detection depend on host environment; incorrect runtime selection could lead to startup failures"],"error_quality":0.0}