aixplain SDK

Build, deploy, and govern autonomous AI agents — in a few lines of Python.

The fastest way to deploy managed, multi-agent systems with runtime governance — on any infrastructure.

aixplain is the operating system for autonomous AI — multi-agent orchestration and runtime governance across cloud, on-prem, edge, and fully air-gapped environments. It spans the full lifecycle — development → evaluation → deployment → monitoring → evolution — so you ship faster instead of stitching tools together. Agents plan, call models and tools, run code, and adapt at runtime, with agents-in-the-loop governance enforced on every execution.

Build any kind of agent on one runtime — knowledge (RAG), data, custom-logic, integration, and team agents — with built-in memory, multimodality, and file handling.

Develop your way — SDK, API, CLI, and MCP environments all run on the same runtime layer, backed by an integrated marketplace of 900+ AI models, tools, and integrations from 70+ vendors (OpenAI, Anthropic, Gemini, Firecrawl, Tavily, SerpAPI, a code-execution sandbox, and more). One API key, one bill, pay as you go — no per-vendor keys or contracts.

Why aixplain

Less to build, less to operate:

• Deploy with one call — agent.save() promotes an agent to a persistent, versioned endpoint; no Dockerfiles, queues, or autoscaling to manage.
• No integration glue — reach 900+ models, tools, and integrations through one key; skip per-provider SDKs, auth, and rate-limit handling.
• Governance you don't have to code — allow-lists, per-asset permissions, rate and usage limits, and enterprise RBAC enforced at runtime.
• Self-debugging — step-level traces of every plan, tool call, and outcome.
• Run it anywhere — the same definition runs serverless, on-prem, at the edge, or fully air-gapped.

Agentic OS

Agentic OS is the portable runtime platform behind aixplain agents — orchestration, governed asset serving, and observability across Cloud (instant), on-prem, edge, and air-gapped deployments. See the documentation for the full architecture.

Quick start

This README documents SDK v2, the default API. SDK v1 (the legacy factory API) keeps working until end of July 2026, after which v2 is the only supported surface.

pip install aixplain

Get your API key from your aixplain account, then expose it to the SDK:

export AIXPLAIN_API_KEY=<your-key>

Create and run your first agent

from uuid import uuid4
from aixplain import Aixplain

aix = Aixplain()  # reads AIXPLAIN_API_KEY from the environment

search_tool = aix.Tool.get("tavily/tavily-web-search/tavily")
search_tool.allowed_actions = ["search"]

agent = aix.Agent(
    name=f"Research agent {uuid4().hex[:8]}",
    description="Answers questions with concise web-grounded findings.",
    instructions="Use the search tool when needed and cite key findings.",
    tools=[search_tool],
)
agent.save()

result = agent.run(
    query="Who is the CEO of OpenAI? Answer in one sentence.",
)
print(result.data.output)

Runs return typed objects — read outputs with result.data.output, not dict indexing.

Build a multi-agent team

from uuid import uuid4
from aixplain import Aixplain
from aixplain.v2 import EditorConfig, EvaluatorConfig, EvaluatorType, Inspector, InspectorAction, InspectorActionConfig, InspectorSeverity, InspectorTarget

aix = Aixplain()  # reads AIXPLAIN_API_KEY from the environment
search_tool = aix.Tool.get("tavily/tavily-web-search/tavily")
search_tool.allowed_actions = ["search"]

def never_edit(text: str) -> bool:
    return False

def passthrough(text: str) -> str:
    return text

noop_inspector = Inspector(
    name=f"noop-output-inspector-{uuid4().hex[:8]}",
    severity=InspectorSeverity.LOW,
    targets=[InspectorTarget.OUTPUT],
    action=InspectorActionConfig(type=InspectorAction.EDIT),
    evaluator=EvaluatorConfig(
        type=EvaluatorType.FUNCTION,
        function=never_edit,
    ),
    editor=EditorConfig(
        type=EvaluatorType.FUNCTION,
        function=passthrough,
    ),
)

researcher = aix.Agent(
    name=f"Researcher {uuid4().hex[:8]}",
    instructions="Find and summarize reliable sources.",
    tools=[search_tool],
)

team_agent = aix.Agent(
    name=f"Research team {uuid4().hex[:8]}",
    instructions="Research the topic and return exactly 5 concise bullet points.",
    subagents=[researcher],
    inspectors=[noop_inspector],
)
team_agent.save(save_subcomponents=True)

response = team_agent.run(
    query="Compare OpenAI and Anthropic in exactly 5 concise bullet points.",
)
print(response.data.output)

Execution order:

Human prompt: "Compare OpenAI and Anthropic in exactly 5 concise bullet points."

Team agent
├── Planner: breaks the goal into research and synthesis steps
├── Orchestrator: routes work to the right subagent
├── Researcher subagent
│   └── Tavily search tool: finds and summarizes reliable sources
├── Inspector: checks the final output through a simple runtime policy
├── Orchestrator: decides whether another pass is needed
└── Responder: returns one final answer

SDK 1 (legacy): available until end of July 2026 — see the SDK 1 docs.

MCP Server Marketplace

aixplain Marketplace now also exposes MCP servers for 900+ models and tools, allowing external clients to access selected tool, integration, and model assets, for example Opus 4.6, Kimi, Qwen, Airtable, and Slack, through aixplain-hosted MCP endpoints with a single API key 🔑.

Read the full MCP setup guide in the MCP servers docs.

{
  "ms1": {
    "url": "https://models-mcp.aixplain.com/mcp/<AIXPLAIN_ASSET_ID>",
    "headers": {
      "Authorization": "Bearer <AIXPLAIN_APIKEY>",
      "Accept": "application/json, text/event-stream"
    }
  }
}

Core concepts

See the documentation for the full API reference.

Data handling and deployment

aixplain applies runtime governance and enterprise controls by default:

• We do not train on your data — your data is not used to train foundation models.
• No data retained by default — agent memory is opt-in (short-term and long-term).
• SOC 2 Type II certified — enterprise security and compliance posture.
• Runtime policy enforcement — Inspector and Bodyguard govern every agent execution, with allow-lists for assets and actions, per-asset permissions, rate and usage limits, and enterprise RBAC.
• Portable deployment options — Cloud (instant) or on-prem (including VPC and air-gapped environments).
• Encryption — TLS 1.2+ in transit and encrypted storage at rest.

Learn more at aixplain Security and aixplain pricing.

Pricing

Start free, then scale with usage-based pricing.

• Pay as you go — prepaid usage with no surprise overage bills.
• Subscription plans — reduce effective consumption-based rates.
• Custom enterprise pricing — available for advanced scale and deployment needs.

Learn more at aixplain pricing.

Community & support

• Documentation: docs.aixplain.com
• Example agents: https://github.com/aixplain/cookbook
• Learn how to build agents: https://academy.aixplain.com/student-registration/
• Meet us in Discord: discord.gg/aixplain
• Talk with our team: care@aixplain.com

License

This project is licensed under the Apache License 2.0. See the LICENSE file for details.