Bifrost is a high-performance AI gateway written in Go, built by Maxim AI, that routes requests across 15+ LLM providers through a single OpenAI-compatible API. It claims 11 µs of overhead at 5,000 RPS, delivers hierarchical budget controls at the org/team/project/key level, and ships native MCP support across all four transports (STDIO, HTTP, SSE, Streamable HTTP). With 4,000+ GitHub stars and Apache 2.0 licensing, it is a credible open-source alternative to LiteLLM for teams prioritizing performance, cost governance, and agentic workflows.
Why It's in Trial
Bifrost addresses a real gap: LiteLLM (the current standard) carries 8 ms P95 latency at 1,000 RPS and a March 2026 supply chain compromise, while Portkey's MCP story is primarily observability. Bifrost is purpose-built for the control plane problems teams actually face when rolling out agentic engineering at scale:
Performance: Go runtime yields ~11 µs gateway overhead at 5,000 RPS — roughly 700× lower than LiteLLM's Python-based proxy under load. Relevant when many agents are making high-frequency calls through a shared gateway.
Hierarchical budgets: Spending limits cascade at four levels — organization → team → project → virtual key. A team can cap org spend at $10K/month, team spend at $2K, and per-key spend at $500, all enforced at the gateway without application-level code.
Virtual key management: Agents and services never receive raw provider API keys; they receive virtual keys that can be rotated or revoked independently. HashiCorp Vault is supported for key storage.
Native MCP gateway: Bifrost exposes an MCP endpoint that bridges to backend providers across all four MCP transports. Uniquely, it includes a Code Mode integration — at 500 tools, generating TypeScript declarations instead of raw definitions saves 92% on tokens (see Cloudflare Code Mode).
Auth and SSO: Google and GitHub OAuth out of the box, no separate IdP integration required.
Observability: Prometheus metrics and distributed tracing; integrates with existing APM stacks without additional sidecars.
Provider coverage: 15+ providers including OpenAI, Anthropic, AWS Bedrock, Google Vertex AI, Azure, Cohere, Groq, and Ollama — covers the vast majority of production traffic, though fewer than LiteLLM's 100+.
vs. the Alternatives
Bifrost
LiteLLM
Portkey
Helicone
Language
Go
Python
TypeScript
TypeScript / Rust
Gateway latency
~11 µs
~8 ms P95
Not published
Near-zero (Rust)
Provider count
15+
100+
200+
100+
Hierarchical budgets
✅ (4 levels)
✅ (per-key/team)
✅
❌
Virtual keys
✅
✅
✅
❌
MCP gateway
✅ (all transports)
Basic
✅ (observability)
❌
SSO
✅
❌ (enterprise tier)
✅
❌
Supply chain concern
None known
⚠️ March 2026 incident
None known
None known
License
Apache 2.0
MIT
Open source (Mar 2026)
Apache 2.0
Stars
4,000+
20,000+
7,000+
5,400+
When to Choose Bifrost
You need a self-hosted gateway with per-team cost governance and don't want to operate a Python service under load
Your agentic engineering platform requires MCP tool serving with centralized auth and per-team access control
You want to issue virtual keys to developers/agents without exposing raw provider credentials
LiteLLM's supply chain history is a blocker for your security team
You're starting greenfield — Bifrost's opinionated structure (org → team → project → key) maps well to an enterprise developer platform
When NOT to Choose Bifrost
You need 100+ provider integrations: LiteLLM's breadth is unmatched (AWS SageMaker, Hugging Face, Together AI, and dozens more not in Bifrost's 15) — though Bifrost's 15 cover ~95% of production traffic for most teams
Your team is deep in the Python/LangChain ecosystem: LangChain, LlamaIndex, and many agent frameworks have LiteLLM auto-detection built in; switching to Bifrost means going proxy-only and losing in-process SDK convenience
Community and battle-tested scale: LiteLLM has 20K+ stars, years of production proof at Netflix and Rocket Money, and a large body of known edge cases documented publicly. Bifrost at 4K stars is newer — you're more likely to hit an undocumented issue
You already run Kong or Traefik as your API gateway and want AI features plugged in rather than a standalone service
Observability-first: if LLM request logging and prompt management are the primary need, Helicone is simpler
Managed, no ops: OpenRouter eliminates all infrastructure; Bifrost requires a deployment
