AI on Upsun

Let Upsun Dispatch^™ plan, code, and review your software with governed AI-agent workflows. Use Upsun Cloud to deploy AI agents, MCP servers, RAG applications, and chatbots. Integrate with Claude, GPT, Gemini, and any LLM API.

Agents

Agentic Automation

Upsun Dispatch

Governed AI-agent workflows that plan, code, review, and optimize your software. Connect a repository, leave a comment, and Upsun Dispatch takes it from there.

Turn issues into pull requests

Comment @upsun-dispatch implement on a GitHub, Jira, or Linear issue and Upsun Dispatch opens or updates a pull or merge request

Automated code review

Upsun Dispatch reviews GitHub pull requests and GitLab merge requests, publishing checks, comments, and summaries

Full visibility into every run

Monitor run status, logs, timelines, and usage from the Upsun Dispatch console

Explore Upsun Dispatch Quickstart

Everyone works from the same run

Captured as it happens. Visible to the whole team, not just whoever kicked it off.

Upsun Dispatch run timeline showing an approved plan step and a live code step

Findings are prioritized and actionable

A summary and recommendation, then findings ranked by impact.

New: AI Observability

Upsun Cloud Performance Agent

Find performance bottlenecks without writing a profiling script or reading through hours of trace data. Get a report with actionable fixes.

Correlates every signal you have

Profiling data, live traffic, and your source code, all analyzed in one pass

Nothing to install

Bring your own LLM API key and get a report in minutes

Findings with suggested diffs

Each report ranks bottlenecks and proposes a code fix, not just a graph

Get Started with the Performance Agent

Tools

Model Context Protocol

Upsun MCP Server

Give Claude direct access to your Upsun infrastructure. Manage projects, environments, and deployments through natural language conversations.

Deploy with natural language

Ask Claude to deploy your app, create environments, or scale resources

Manage infrastructure

Query logs, check metrics, and troubleshoot issues conversationally

Works with Claude Desktop

Seamless integration with your existing AI assistant workflow

Get Started with MCP All install options

terminal

# Add the Upsun MCP Server

$ claude mcp add —transport http upsun https://mcp.upsun.com/mcp

# Now ask Claude to deploy

You: “Deploy my Next.js app to production”

✓ MCP Server connected
✓ Found project: my-nextjs-app
✓ Creating environment: main
✓ Deploying application…
✓ Deployment complete!

Claude Code CLI

# Deploy with slash commands

claude> /upsun deploy —environment=main

Building application ‘myapp’…
Provisioning services…
✓ Deployed to main

# Check environment status

claude> /upsun status

Claude Code Integration

Upsun Skill for Claude Code

Deploy directly from your terminal with Claude Code CLI. Manage your entire Upsun infrastructure without leaving your development environment.

Slash command interface

Simple commands like /upsun deploy for instant deployment

Integrated workflow

Code, test, and deploy without context switching

Full environment control

Create, merge, and manage environments from the command line

View on GitHub

Apps

terminal — bash

Quick Start: Deploy an AI Agent

Get started with a simple Python AI agent that integrates with the Anthropic API.

.upsun/config.yaml

applications:

ai-agent:

type: “python:3.12”

relationships:

database: “db:postgresql”

hooks:

build: |

pip install anthropic flask

web:

commands:

start: “python app.py”

services:

db:

type: postgresql:16

app.py

import anthropic

import os

client = anthropic.Anthropic(

api_key=os.environ[“ANTHROPIC_API_KEY”]

)

message = client.messages.create(

model=“claude-3-5-sonnet-20241022”,

max_tokens=1024,

messages=[

]

)

# Set your API key as an environment variable

$upsun variable:create —level environment —name ANTHROPIC_API_KEY —value “your-key”

# Deploy to Upsun

$git push upsun main

Building application ‘ai-agent’…

Provisioning PostgreSQL database…

✓ Deployment complete

https://main-abc123.us-5.platformsh.site/

Full AI Agent Tutorial

Use Cases

What You Can Build

Deploy any AI application that integrates with LLM APIs. Upsun provides the infrastructure, databases, and networking you need.

AI Agents & Chatbots

Deploy conversational AI powered by Claude, GPT, or Gemini with persistent chat history and context management.

MCP Servers

Host Model Context Protocol servers that extend Claude Desktop and other AI tools with custom capabilities.

RAG Applications

Build retrieval-augmented generation apps with vector databases like Chroma and Qdrant for context-aware AI responses.

Supported Technologies

Build with your preferred stack. Any language, any LLM, any database.

Runtimes

PythonNode.jsPHPGoRubyJava

LLM Providers

ClaudeGPT-4GeminiAzure OpenAIBedrock

AI Frameworks

LangChainLlamaIndexHaystackSemantic Kernel

Vector Databases

pgvectorChromaQdrantRedisMongoDB

CPU-optimized for AI orchestration. Call external LLM APIs for GPU-intensive inference. Your app handles business logic, data processing, and UX — cost-effective and easy to scale.

Learn More

Resources & Tutorials

AI Agent Guide

Complete guide to deploying conversational AI agents with persistent memory

Deploy MCP Servers

Host Model Context Protocol servers for Claude Desktop and other tools

Building AI Agents Tutorial

Production RAG application with vector search and intelligent context

Vector Databases

Set up Chroma, Qdrant, or pgvector for embeddings storage

AI Blog Posts

Latest AI tutorials, best practices, and case studies

Community Forum

Get help and share your AI projects with the community

Ready to Deploy Your AI Application?

Start building AI agents, MCP servers, and intelligent applications on Upsun today.

Start Tutorial →Browse Examples