Build AI agents that
actually do the work.
Give an agent an LLM, 254 live MCP tools, and a workflow. It perceives, reasons, and acts — autonomously. Deploy as a REST endpoint in one click.
From prompt to autonomous agent.
Configure the agent
Set a system prompt, choose an LLM, and attach MCP tools. The agent loop runs automatically — no code needed.
Connect tools & workflows
Wire up MCP servers for live integrations. Add workflow nodes for branching, loops, approvals, and sub-agent delegation.
Deploy & call
Run the agent via chat, webhook, schedule, or a dedicated REST endpoint. Set up pay-per-call if consumers will call it directly.
Learn more about how autonomous AI agents work or see a coding agent in action.
Everything an AI agent needs. All in one platform.
LLM + MCP tools + workflows
Agents run the full perceive–reason–act loop. The LLM reasons over a task, decides which MCP tool to call, receives the result, and iterates — all inside a 30-node workflow engine.
Deploy as a REST endpoint
Turn any agent into a callable API in one click. Set it to free or paid — consumers pay per call from a wallet. No billing code to write.
Multi-agent teams & delegation
A lead agent can hand off sub-tasks to specialist agents. Each has its own tools and persona. Results compose automatically — no orchestration glue.
Guardrails + human approval
Insert approval gates anywhere in a workflow. The agent pauses, routes to a human reviewer, and resumes on approval — keeping automation safe for high-stakes tasks.
Perceive → Reason → Act → Repeat.
Every Aerostack agent runs the same core loop: the LLM reads context, decides which MCP tool to call, executes it, incorporates the result, and keeps going — until the task is done or a human approval gate fires.
What teams build on Aerostack.
These are representative agent templates — use them as a starting point or build your own from scratch.
PDF Analyzer
Upload documents, extract key insights, answer questions from content. Built with RAG + vector search.
E-commerce Assistant
Product recommendations, order tracking, refund processing. Connects to Shopify + Stripe via MCP.
Code Review Agent
Automated PR reviews with security scanning, style checks, and suggested fixes.
Analytics Reporter
Daily/weekly reports from Mixpanel, PostHog, or GA4. Summarized insights delivered to Slack.
Email Outreach Agent
Personalized cold email sequences based on prospect research. Connects to HubSpot + SendGrid.
Research Assistant
Deep web research, source verification, structured reports. Multi-step workflows with human review.
Turn any agent into a callable API.
Agent Endpoints expose your agent as a REST API. Set it to free or charge per call — consumers pay from a wallet balance with no extra billing setup on your end. Ideal for teams that want to let other services trigger an agent programmatically.
Related features
Frequently asked questions
What is the Aerostack AI agent platform? +
Aerostack is a platform for building and deploying autonomous AI agents. Agents run a perceive–reason–act loop powered by an LLM, call live MCP tools, chain steps in a visual workflow, and can hand off tasks to other agents or request human approval.
How do I build an AI agent on Aerostack? +
Create an agent in your workspace, attach a system prompt and an LLM model, then connect MCP tools and workflow nodes. The agent loops autonomously — perceiving inputs, reasoning, and calling tools — until the task is complete. No code required for most use cases.
Can I expose an agent as a REST API endpoint? +
Yes. Any agent can be turned into a callable REST endpoint via Agent Endpoints. You can set the endpoint to free or paid (price_per_run_cents). Consumers call the endpoint from a wallet balance — no billing integration needed on your side.
What MCP tools can agents use? +
Aerostack provides over 254 MCP tools covering GitHub, Slack, Notion, Google Workspace, databases, web search, and more. Agents in a workspace automatically have access to all MCP servers installed there.
How do multi-agent teams work? +
A lead agent can delegate sub-tasks to specialist agents via bot-to-bot delegation. Each agent in the team has its own tools and prompt. Results are passed back and composed into a final output — no manual orchestration code needed.