The Cloud Backend for AI Agents.
Stop building custom wrappers for memory and tool execution. Neonia is a managed MCP backend that gives your LLMs zero-trust WebAssembly compute, persistent Graph Memory, and token-saving data pointers (neonia://).
Time-to-Value in 1 Minute
Zero Docker config. No local Python environments. Just plug in the API key.
import os from mcp import ClientSession from mcp.client.streamable_http import streamable_http_client from langgraph.prebuilt import create_react_agent # 1. Connect to Neonia Cloud OS securely headers = { "Authorization": f"Bearer {os.environ.get('NEONIA_API_KEY')}" } async with streamable_http_client("https://mcp.neonia.io/mcp", headers=headers) as (read, write): async with ClientSession(read, write) as session: await session.initialize() # 2. Equip Agent with Governed Graph Tools tools = await session.list_tools() agent = create_react_agent(model, tools) # 3. Execute with Zero-Token Reasoning await agent.ainvoke({ "messages": [ ("user", "Query the swarm's Governed Graph Memory " "to find the exact deterministic fix for ERR_504.") ]})
Stop duct-taping infrastructure.
The OS Base Layer is Free.
Developers hate setting up local infrastructure. Skip the Pinecone, Redis, and Docker setup. We provide the batteries included, free forever.
Governed Graph Memory
Free persistent memory for your agents powered by SurrealDB. Forget about local JSON files and RAG hallucinations.
Agentic Queues (Pub/Sub)
Built-in robust message queues. Let your agents delegate tasks and work asynchronously across different environments.
System MCP Tools
Core OS utilities (file parsing, data manipulation, validation) are available directly from the cloud with Zero Setup.
Agent-Native Economy
No Subscriptions
SYSTEM LAYER (MEMORY & QUEUES) IS 100% FREE. Scale your agents up or down without commitment. Only pay for the Wasm compute your agents actually consume.
Agent-Native Billing
Pay-per-invocation logic handled via the HTTP 402 protocol. Top up a single developer balance and let your agents execute tools atomically with $0.001 precision.
On-Demand Tool Generation
Request missing tools directly through the MCP. Fully refunded if the API is technically unfeasible or restricted.
From isolated scripts to a native Agentic Platform.
Local setups isolate your agents, bloat your prompts, and burn tokens on raw data routing. Neonia provides a unified data bus where infinite tools, async queues, and shared memory communicate natively.
Architectural Pillar
🧩Fragmented Local Setup
(The Old Way)
🚀Neonia Cloud OS
(The Closed Loop)
Tool Capacity & Prompt Bloat
Hardcoded & Limited. Injecting 20+ tool schemas directly into the System Prompt burns thousands of tokens per request and causes LLM amnesia.
Infinite Auto-Discovery. Inject just one tool (neonia_sys_tool_discovery). Agents dynamically pull capabilities from our massive library JIT (Just-In-Time).
Data Flow (Token Arbitrage)
LLM as a Router. Tools send massive 5MB raw JSONs back to the LLM context just to be passed to the next tool. Extremely expensive.
Native Edge Piping. Tools communicate natively on the Neonia backend. A Wasm filter extracts 2KB of pure insight before hitting your LLM.
Swarm Coordination
Synchronous & Brittle. Requires heavy orchestrators (LangGraph) or setting up local Redis servers just to pass a single message between agents.
Native IPC Queues. Asynchronous task handoff. Agent A pushes a task to neonia_sys_queue_push, goes to sleep, and Agent B picks it up globally via neonia_sys_queue_pop.
Global Memory & State
Isolated & Unstructured. Agents dump basic facts, logs, and complex rules into a single messy local database. This unstructured text blob leads to LLM hallucinations. Agent B cannot access Agent A's state.
The Dual-Memory Shared Brain. Explicit cognitive routing. Agents autonomously separate cheap semantic state (neonia_sys_memory_note) from hard-learned causal rules (neonia_sys_memory_lesson). When one agent solves a problem, the global Swarm instantly inherits the exact Cause and Effect.
The Autonomous Flywheel: One Connection, Infinite Scale
A single tool is just a utility. A native ecosystem is an unfair advantage. Watch your agents self-orchestrate without writing any glue code:
1. Discover
The agent realizes it needs to parse complex HTML. It uses Auto-Discovery to pull a Neonia Web Scraper dynamically.
2. Native Compute
It fetches a 10MB page and pipes it directly into a Wasm Filter. Raw data never hits the LLM context. Tokens saved.
3. Delegate
It drops the extracted 2KB insight into an asynchronous Task Queue for a specialized Analyst Agent to pick up.
4. Evolve
It stores the extraction logic in Shared Cloud Memory, ensuring the Swarm instantly knows how to handle this site.
All this happens through a single standard MCP connection. Zero local infrastructure.