Built it yourself
3–6 months of agent plumbing: orchestration, memory, tool calling, retries, observability. Your product waits while your team rebuilds infrastructure.
Open infrastructure for AI agents
Open-source AI agent infrastructure that runs in production.
Build, connect, and run AI agents with multi-agent orchestration, MCP tools, grounded knowledge, and persistent memory — on your infrastructure or ours. One Go binary, your models, your data. Your coding agent can install it over MCP in minutes.
Open-source core Any LLM REST + SSE MCP-native
Live demo: your coding agent installs SyntheticBrew over MCP, then the agent answers with real tool calls. Hover to pause.
Works with OpenAI Anthropic Google Gemini DeepSeek Mistral Ollama + any OpenAI-compatible API
The production gap
AI agent orchestration without months of infrastructure work
An AI agent demo takes a day. The runtime behind it — sessions, memory, tool execution, recovery, audit — takes months. SyntheticBrew ships that runtime as one system your team can inspect and operate.
Closed cloud platforms
$500–2,000/mo with per-token markup that scales with usage. Your product and customer data leave your environment, and the runtime belongs to someone else.
Python frameworks
A library, not a product. No REST API, no admin UI, no session persistence. You are still building the runtime — and every upgrade risks breaking changes.
AI agent builder
No-code AI agent builder: describe it, inspect every decision
The AI builder turns a plain-language brief into agents, tools, memory, and flows. The visual canvas keeps the result understandable and editable before you ship it.
- Generate a supervisor and specialist agents from one prompt.
- Bind MCP tools and models with explicit scopes.
- Add gates, delegation, and persistent memory visually.
- Test the real run in chat with every tool step visible.
Platform features
AI agent capabilities: reason, act, remember, recover
Use the complete runtime or start with the capability blocking your team today. Each feature shares one API, one operational model, and one deployment choice.
Visual and prompt-driven Specialists that work together Connect tools once Context across sessions Ground answers in evidence Typed, deterministic retrieval See every step Boundaries before autonomy Headless by design Your infrastructure, your keys
AI Agent Builder
Describe the outcome in plain English. SyntheticBrew proposes agents, tools, flows, gates, and memory—then lets your team inspect and refine every part in a visual canvas.
Multi-Agent Orchestration
Build teams of specialized agents that delegate work, use narrowly scoped tools, pass results through gates, and stream their progress to your product.
MCP Integration
Register MCP servers, assign tools to the right agents, forward the user’s auth context, and execute every call on the server—without turning your frontend into an orchestrator.
AI Agent Memory
Let agents remember customers, decisions, and working context across sessions while keeping memory isolated by schema and stored in your PostgreSQL deployment.
Agentic RAG
Upload your documents, isolate knowledge per schema, and let agents retrieve evidence automatically while reasoning and using tools.
Knowledge Graphs
Declare categories, attributes, and relationships as a typed domain model. SyntheticBrew generates MCP tools that let agents retrieve exact records instead of guessing identifiers.
Agent Observability
Follow reasoning, sub-agent delegation, tool calls, results, errors, and completion in real time—then retain an operational record for debugging and review.
Agent Security
Treat every tool call as a privileged operation. Scope access per agent, forward the user’s identity to your backend, and require confirmation before consequential actions.
Product Integrations
Keep your frontend and domain APIs. Add SyntheticBrew as a headless agent runtime through standard HTTP and structured server-sent events.
Self-Hosted AI
Deploy the complete agent runtime with your own PostgreSQL, model keys, network controls, and operational stack—without rebuilding orchestration, memory, or tool execution.
MCP integration
MCP integration: give AI agents tools without losing your security model
SyntheticBrew executes MCP tools server-side, forwards the authenticated user and organization context, and pauses before configured destructive actions.
- Connect HTTP, SSE, streamable-HTTP, and stdio MCP servers.
- Scope tool access separately for every specialist.
- Forward Authorization, org, user, and custom tenant headers.
- Stream tool calls, results, and confirmations to any frontend.
A thin integration surface
How to integrate an AI agent into your app
Your frontend sends one message. The runtime reasons, delegates, calls tools, waits for confirmation when required, persists the session, and streams typed events back. No client-side tool executor is required.
- Standard REST request
- Structured server-sent events
- Any web, mobile, or backend client
POST /api/v1/agents/support/chattext/event-stream
// Your product sends one request data: {"type":"agent_spawn","agent":"account-agent"} data: {"type":"tool_call","tool":"account.lookup"} data: {"type":"tool_result","status":"completed"} data: {"type":"message_delta","content":"I found…"} data: {"type":"done","session_id":"sess_abc"}
Solutions
AI agent use cases: customer service, ecommerce, banking, IoT — and any workflow in your product
These are the patterns we document in depth, but the runtime is domain-agnostic: if the workflow lives behind an API, an agent can work it — grounded and permission-aware.
Comparing tools? See how SyntheticBrew stacks up against Dify, LangChain, n8n, and the other approaches — or learn how to build an AI agent from scratch.
Real named deployment
Powering the AI layer in Kilo AIoT
SyntheticBrew is the agent engine behind Kilo’s permission-scoped device questions, rule and alarm workflows, confirmation before consequential actions, and result verification after writes.
Kilo application
SyntheticBrew agents
Scoped MCP tools
Device & operations APIs
Dogfooded — our AI builder runs on SyntheticBrew Live examples — try working agents → Open examples on GitHub ↗
One engine, three paths
Self-hosted AI agents, managed Cloud, or built for you
The same production runtime is available as Cloud, an open-source self-hosted deployment, or a hands-on implementation delivered into your product.
Use Cloud
Register and start building without operating the platform yourself. Free tier with 100 monthly active users, unlimited messages, bring your model keys — no token markup.
Self-host
Run Community Edition with your infrastructure, PostgreSQL, model keys, and network controls. Free forever, no runtime meter — install with Docker or let your coding agent do it over MCP.
Have us build it
Book directly into Tim’s Calendly and scope a production implementation delivered to a measured acceptance bar.
From agent idea to production runtime.
Build with your model, your tools, and your deployment choice—without asking your product team to recreate agent infrastructure.