Arcee Bridge: Best AI API Gateways for AI Developers in 2026

What Is Arcee Bridge?

Arcee Bridge is an open-source AI API gateway built in Go by xn030523 that automates Arcee AI account creation using YYDS Mail disposable emails and proxies requests via an OpenAI-compatible interface. It handles full registration flow including email verification and token extraction, then serves endpoints like /v1/chat/completions and /v1/models with Bearer auth. Arcee Bridge is one of the best AI API gateways for AI developers integrating Arcee models into existing OpenAI SDKs or clients without manual signup. With 47 GitHub stars and 29 forks as of April 2026, it targets proxy experiments and codex layers.

Quick Overview

Who Should Use Arcee Bridge?

• AI experimenters prototyping with Arcee models who need instant OpenAI compatibility without browser-based registration.
• Indie hackers building LLM chains that require disposable accounts for rate-limit evasion or testing.
• DevOps teams automating AI gateway deployment in local or server environments with config-driven token management.
• OpenAI client users swapping providers seamlessly via model name mapping like trinity-large-thinking.

Not ideal for:

• Production workloads demanding 100% OpenAI spec compliance, as it supports only core chat and models endpoints.
• Users needing multi-provider routing, where tools like LiteLLM handle dozens of APIs.
• Teams avoiding Go binaries, preferring Python-based proxies.

Key Features of Arcee Bridge

• Automated Signup Workflow — Creates YYDS Mail inbox via API key, registers Arcee account, polls for verification email, extracts link from raw message, verifies, logs in, and saves token to access_token.json in one go run . command.
• OpenAI-Compatible Server — Listens on 0.0.0.0:8787 by default, exposes /v1/chat/completions POST for streaming responses, /v1/models GET for listing with Bearer daiju auth, and /models alias.
• Config-Driven Operation — config.json sets mode (signup/serve), signup.api_key for YYDS, server.enabled_tools array like ["web_search"] passed to Arcee, and base_model_name for default mapping.
• Token Persistence — Serve mode reads access_token from config.json or access_token.json (auto-generated with email, password, verify_link, created_at), enabling reuse without re-registration.
• Minimal Tool Support — Forwards web_search tool flag to Arcee requests, suitable for basic agent experiments without full OpenAI tools spec.
• Health Check Endpoint — GET /healthz confirms server status post-launch.
• Local Tool Runtime — Supports running local tools alongside, per local_tools.go implementation.

Arcee Bridge vs Alternatives

LiteLLM suits broader integrations by proxying OpenAI, Anthropic, and others with virtual keys, but lacks built-in account automation—pair it with browse all AI API Gateways for Arcee Bridge workflows. OpenRouter handles pay-per-token across providers without local setup, ideal for cloud-only teams avoiding self-hosting. Portkey adds metrics and retries for scale, but requires paid plans beyond basics.

How Arcee Bridge Works

Arcee Bridge splits into signup and serve modes orchestrated via main.go, which parses flags like -mode serve and loads config.json. Signup flow in signup.go uses yydsmail package (client.go, mailbox.go, messages.go) to generate @xiaodai.eu.cc inbox, POSTs to Arcee register endpoint, polls /messages every few seconds for verify email, parses HTML with inspect.go for https://api.arcee.ai/app/v1/verify-email/... link, GETs it for 200 status, then logs in via /login for access_token. Token saves to access_token.json with ISO timestamp like "2026-04-02T10:00:00+08:00".

Serve mode in server.go reads token, wraps Arcee client (arcee/client.go, flow.go, chat.go), maps requests to /v1/chat/completions by injecting base_model_name and enabled_tools, streams responses with OpenAI JSON format. Config module (config/config.go) handles JSON I/O, .gitignore excludes tokens. Core abstraction: thin HTTP proxy with auth prefix Bearer {server.openai_api_key}, no persistent state beyond files.

# Quickstart: signup (replace with your YYDS api_key in config.json)
go run .

# Output example:
signup [email protected]
password=xxxxx
verify_link=https://api.arcee.ai/app/v1/verify-email/xxxx
verified status=200
access_token=xxxx

# Serve mode
go run . -mode serve

Signup creates and verifies account in ~30-60 seconds depending on email polling (default interval unspecified, tunable via code). Serve binds to port 8787 across interfaces; test with curl http://127.0.0.1:8787/v1/models -H "Authorization: Bearer daiju" listing models like trinity-large-thinking. Initial config copy from config.json.ex sets domain and tools.

Pros and Cons of Arcee Bridge

Pros:

• Zero-manual registration: Full chain from email creation to token in one CLI run, saving 5-10 minutes per setup versus browser flows.
• Lightweight Go binary: Single go run no deps install, <10MB footprint, runs on Linux/Mac without Docker.
• OpenAI drop-in: /v1/chat/completions accepts standard payloads, works with openai Python/JS SDKs unchanged.
• Configurable tools: Passes web_search flag directly, enables Arcee agents without custom wrappers.
• Token reuse: Serve mode auto-loads prior access_token.json, supports repeated proxy runs.
• Local-first: No cloud deps beyond Arcee/YYDS APIs, offline token use post-signup.

Cons:

• Arcee-only: No multi-provider support, unlike LiteLLM's 50+ backends.
• Incomplete OpenAI spec: Lacks /v1/completions, embeddings, images; chat/models only.
• YYDS dependency: Requires api_key from linux.do community, potential single-point failure if service down.
• No streaming metrics: Raw proxy passthrough, no request logging or latency tracking.
• Token exposure: access_token.json plaintext, gitignored but risky on shared hosts.

Getting Started with Arcee Bridge

Clone repo and prep config:

git clone https://github.com/xn030523/arcee
cd arcee
cp config.json.ex config.json
# Edit config.json: add your YYDS signup.api_key from https://linux.do/

Run signup:

go run .

Outputs email/password/verify_link/token, generates access_token.json. Then serve:

go run . -mode serve

Server runs at http://0.0.0.0:8787. Verify:

curl http://127.0.0.1:8787/healthz
curl http://127.0.0.1:8787/v1/models -H "Authorization: Bearer daiju"

Post-start, config server.listen for custom port/IP, set enabled_tools for web_search. First chat: POST /v1/chat/completions with model: trinity-large-thinking, streams Arcee response. Re-run signup overwrites token if needed.

Verdict

Arcee Bridge is the strongest option for AI developers needing instant Arcee access in OpenAI clients when avoiding manual registration matters most. Its end-to-end signup automation and minimal Go proxy deliver reliable localhost:8787 gateway in under a minute. Pick it for prototypes, but switch to LiteLLM for production multi-LLM needs.