yomorun/yomo

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

1920 stars · 148 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

YoMo is an open-source serverless LLM function calling framework for building fast, geo-distributed AI agents, written in Rust with a QUIC-based runtime. It lets developers deploy LLM tools/skills (in TypeScript or Go), expose them as MCP servers, and route AI model traffic through an OpenAI-compatible API.

Use cases

• build ai agents with llm function calling
• deploy serverless llm tools close to users
• expose llm function calling as an mcp server
• run an openai-compatible chat completions endpoint backed by custom tools
• route llm tool calls across geo-distributed edge infrastructure
• use ollama or openai as provider for agent backends

When to choose

• you need low-latency, geo-distributed execution of LLM tools
• you want to build agents with function calling in TypeScript or Go
• you want MCP server support and OpenAI-compatible APIs in one runtime

When to avoid

• you need a simple single-process agent without distributed deployment
• you require a permissively licensed dependency (no license file is published)
• your stack is Python-only and you don't want TypeScript/Go tool implementations

Facets

framework · maturity active

agent-framework llm-inference mcp rpc http-server cli sdk artificial-intelligence large-language-models developer-tools backend microservices windows cross-platform cli self-hosted llm-function-calling serverless quic edge-ai geo-distributed tool-routing openai-compatible a2a-protocol ai-agents linux macos docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="yomorun/yomo")