Table of Contents
MCP (Model Context Protocol) servers and self-hosted LLM infrastructure are complementary, not alternatives. MCP servers expose tools / data; self-hosted LLMs consume them as agents. Most production deployments include both layers.
MCP servers: wrap your internal tools / databases / APIs with standard tool-discovery protocol. Self-hosted LLMs: consume MCP servers via vLLM + MCP middleware or LangChain / CrewAI / AutoGen. Layers compose: build internal MCP servers; LLMs (self-hosted or hosted) consume them. Trend: MCP becoming standard agent integration layer.
Relationship
- MCP server: exposes tools / resources / prompts via standard protocol
- LLM client: discovers + invokes MCP servers; can be self-hosted or hosted
- Multiple MCP servers: one LLM session connects to many MCP servers (filesystem, database, API wrappers, etc.)
- Self-hosted LLM + own MCP servers: full-stack ownership; data flow stays internal
Deployment
Common deployment shapes:
- Self-hosted vLLM + internal MCP servers: full control; UK / EU residency clean
- Self-hosted vLLM + Anthropic-distributed MCP servers: mix; some external integrations via MCP
- Hosted Claude + internal MCP servers: hosted LLM but internal data via MCP
- Hybrid: most production teams — self-hosted bulk + frontier API for hardest cases; both consume same MCP servers
Verdict
MCP and self-hosted LLM compose cleanly. Build internal tools as MCP servers; serve LLMs as needed (self-hosted primary, frontier fallback). Standard architecture for agentic AI in 2026; vLLM + MCP middleware maturing through 2026.
Bottom line
MCP + self-hosted compose. See MCP tutorial.
