1flowbase
Active·★ 279·Apache-2.0·Updated 2026-10-22
★ Hidden Gem
1flowbase is a self-hosted, low-code AI gateway and application runtime that enables building complete application systems, workflows, and React UIs on top of unified model access and retained conversation data. It's designed API-first, allowing agents to manage and interact with every runtime operation via an MCP gateway.
1flowbase sits in the Workflow Automation category, so it is usually better judged by workflow fit, deployment style, and team needs than by isolated features alone. Based on the available metadata, it leans most clearly toward Unified AI Gateway with Data Retention: Unifies model access and stores full AI conversations, creating reusable data assets for analysis, evaluation, and development.. A representative use case is Building AI Gateway Solutions: Deploying as a multi-model router or enterprise AI gateway to unify access and manage AI models.. The listed license is Apache-2.0. GitHub stars are currently 279. Relevant tags include AI Gateway, Low-code.
#AI Gateway#Low-code#Application Backend#Workflow Automation#Multi-Agent System#Self-hosted#React#API-first
01
Features
01Unified AI Gateway with Data Retention: Unifies model access and stores full AI conversations, creating reusable data assets for analysis, evaluation, and development.
02Composite Models & Workflow Orchestration: Enables combining high-capability models for planning/judging with low-cost models for execution, publishing them as virtual models or tools.
03Agent-Native API Design (MCP Gateway): Every runtime operation is API-based and exposed to agents via an MCP gateway, supporting progressive tool discovery.
04Low-code Efficiency with Native React Flexibility: Combines dynamic business table creation with the freedom of native React code blocks for UI development, avoiding closed drag-and-drop editors.
05Protocol Conversion: Provides conversion between major AI model protocols (Anthropic Messages, OpenAI Chat Completions, and OpenAI Responses), ensuring application layer stability regardless of provider changes.
02
Why choose it
+Unified AI Gateway with Data Retention: Unifies model access and stores full AI conversations, creating reusable data assets for analysis, evaluation, and development.
+Composite Models & Workflow Orchestration: Enables combining high-capability models for planning/judging with low-cost models for execution, publishing them as virtual models or tools.
+Building AI Gateway Solutions: Deploying as a multi-model router or enterprise AI gateway to unify access and manage AI models.
+Supports 8 platforms or runtime environments.
03
Trade-offs
!The final decision should still be made through side-by-side comparison with similar tools.
04
Compatibility
OpenAI
Model API
Verified via docs
Anthropic Claude
Model API
Verified via docs
Docker
Deployment
Verified via docs
PostgreSQL
Database
Verified via docs
Rust
Backend Runtime
Verified via docs
Node.js
Frontend Runtime
Verified via docs
05
Quick start
1
$ curl -fsSL https://raw.githubusercontent.com/taichuy/1flowbase/main/scripts/shell/docker-deploy.sh | sh
06
Use cases
↳Building AI Gateway Solutions: Deploying as a multi-model router or enterprise AI gateway to unify access and manage AI models.
↳Developing Agent Application Backends: Creating application backends specifically designed for AI agents, enabling them to control and interact with the system via APIs.
↳Creating AI Education Platforms: Establishing platforms for AI learning and development, leveraging conversation data and custom applications.
↳Developing Custom Self-hosted AI Applications: Building private, customizable AI applications with integrated workflows, APIs, business data, and React UIs.
07
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