LLM Provider MCP server

Multi-LLM Provider for Go

multi-llm-provider-go is a Go library for using hosted LLM APIs and local coding agents through a shared set of provider interfaces.

It supports two complementary ways to run a model:

transport, including OpenAI, Anthropic, Bedrock, Vertex AI, Azure, and OpenRouter.

• API providers call hosted models through their normal SDK or HTTP

local tmux sessions, preserving their native tools, subscriptions, project context, and authenticated sessions.

• Coding-agent providers run Claude Code, Codex CLI, Cursor Agent, or Pi in

The repository also includes llm-provider-mcp, an optional MCP server for delegating asynchronous work between coding agents. It is one way to expose the provider library—not the library's only use case.

Why This Exists

Applications should be able to choose the right model and transport for each task without rebuilding their orchestration layer.

Use a direct API when you want a conventional request/response integration, predictable infrastructure, or model-level features such as structured output, embeddings, and media generation. Use a coding-agent CLI when you want an agent that can inspect a repository, edit files, run commands, and reuse an existing local subscription. Both fit behind the same Go model abstraction.

flowchart LR
    App[Go application] --> Provider[Shared provider interfaces]
    Provider --> API[API and cloud adapters]
    Provider --> CLI[Local coding-agent adapters]
    API --> Hosted[Hosted models]
    CLI --> Tmux[tmux sessions]
    Tmux --> Agents[Claude Code / Codex / Cursor / Pi]
    MCP[Optional MCP server] --> CLI

Supported Providers

The core InitializeLLM factory returns the same llmtypes.Model interface for text and coding-agent providers:

Specialized factories expose capabilities that do not fit the text-model interface:

Gemini models are available through Vertex AI for direct API access or through Pi as a coding agent. The old Gemini CLI adapter has been removed.

Common Capabilities

Provider support varies, but the shared interfaces cover:

• Text generation and streaming
• Tool calling and structured output
• Token usage, model metadata, logging, and event emission
• Embeddings
• Image input and generation
• Video generation and conversational video editing
• Audio generation and transcription
• Music generation
• Stateful coding-agent sessions, continuation, and terminal progress

Quick Start: Go Library

Install the module:

Shortened. The full README is on GitHub.