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Set up your AI engineering team on Open Source Cloud

Bring the Claude or Codex you already pay for. Paste these prompts. In one session you get a full AI engineering team and your first app deployed, on infrastructure you own.

Step 0 β€” Connect OSC

Connect OSC to your AI tool before pasting the prompts below. Your AI will confirm when the connection is ready.

Claude Code
claude mcp add --transport http osc https://mcp.osaas.io/mcp
Codex β€” add to ~/.codex/config.toml
[mcp_servers.osc]
url = "https://mcp.osaas.io/mcp"

After adding, start Codex, complete the OAuth login, and run /mcp to confirm.

Prompt 1 β€” Connect OSC and build your agent team

You are setting up a new AI agentic-engineering project for me, backed by Open Source Cloud (OSC). Follow these steps in order. Do not write application code yet, this step only connects OSC, asks me what we are building, and creates the team.

STEP 0 - Connect OSC (hard gate).
Call the OSC MCP tool `get-mcp-help`. If it returns the OSC onboarding doc, OSC is connected, continue.
If the tool is missing, STOP and tell me to add it, then wait for me to re-paste:
  - Claude Code: run `claude mcp add --transport http osc https://mcp.osaas.io/mcp` (or add an HTTP MCP connector named `osc` at https://mcp.osaas.io/mcp in Settings), complete the OAuth login, then run `/mcp` to confirm.
  - Codex: there is NO `codex mcp add` for remote servers (that subcommand is stdio-only). Add this block to `~/.codex/config.toml` (or `.codex/config.toml` to scope it to one project), then start Codex, complete the OAuth login, and run `/mcp` to confirm:
    [mcp_servers.osc]
    url = "https://mcp.osaas.io/mcp"

STEP 1 - Understand the project.
Ask me, one question at a time: (a) what am I building and for whom, (b) the one success metric, (c) which surfaces it needs (backend API, web frontend, mobile, data pipeline, MCP server), (d) the time horizon (proof of concept, MVP, production). Propose a sensible default for each and let me accept or change it.

STEP 2 - Build the agent team (use your tool's native convention).
Create a full engineering team. In Claude Code, write one sub-agent file per role under `.claude/agents/<role>.md` with name, description, model, and a minimal tool list. In Codex, define the same roles in `AGENTS.md` and adopt the right role per task.

Mandatory roles: architect, backend, frontend, reviewer, qa, pm, ux, security, and a team-lead (orchestrator for work spanning 3 or more subtasks). Add a domain-specialist role for each real domain in my project (payments, video, auth) and a user-persona role for each distinct end user.

Team rules (bake these into every role and into CLAUDE.md or AGENTS.md):
  - Default every role to the latest model. Security stays on a non-Opus model with high reasoning effort.
  - The reviewer NEVER writes or edits what it reviews, but it CAN run read-only checks to verify against ground truth.
  - Verify before claiming: read the relevant source before writing code that depends on it.
  - After any agent opens a pull request, the reviewer runs automatically before done. Reviewing is not skippable.
  - Never force-push, hard-reset, or run destructive git.
  - Acceptance criteria live in each task, not in the role files. Keep role files timeless.

STEP 3 - Write CLAUDE.md (and AGENTS.md) with the project purpose, the success metric, the team roster, and the rules above. Then stop and tell me to paste Prompt 2.

Prompt 2 β€” Architect your OSC stack (ADR-001)

Act as the architect agent. Decide the Open Source Cloud stack for this project and record it as an Architecture Decision Record, ADR-001.

1. Re-read CLAUDE.md or AGENTS.md and the project purpose.
2. Call `list-service-categories` (live, never trust a cached count) and `list-available-services` to see what OSC offers today. Call `ask-osc-architect` with my problem for guidance, and `list-solutions` or `describe-solution` to check for a pre-baked fit.
3. Propose the stack: which OSC catalog services back this project (database, cache, object storage, search, auth, analytics), whether the app runs as an OSC My App, and whether to enable Agentic SDLC. For each choice give a one-line reason. Flag anything OSC does NOT cover today as an open question, do not invent a service.
4. Write it to `docs/architecture/ADR-001-osc-stack.md` (Context, Decision, Consequences, Alternatives). Show me the summary and wait for my approval before anything is provisioned.

Prompt 3 β€” Ship and deploy on OSC

Act as the team-lead. Execute ADR-001's deploy plan on OSC. Backing services and the app run ON OSC from day one, not later, no long-lived local docker as the default backend.

1. `setup-parameter-store` (one store for this project).
2. For each backing service in ADR-001: `create-service-instance`, then `set-parameter` for its connection string (DATABASE_URL, REDIS_URL). `create-storage-bucket` if object storage is in the ADR. `schedule-backup` before any service holds real data.
3. Have the dev agents build the smallest end-to-end slice that proves the app works against those OSC services.
4. Push the code to my git repo, then `create-my-app` pointed at it and `wait-for-app-ready`. This deploy is the moment my OSC workspace goes live.
5. If ADR-001 chose it, `enable-agentic-sdlc` so the app can keep maintaining itself.
6. Report the live app URL and what each agent did.

What is Agentic Engineering?

Agentic engineering is a software development discipline in which AI agents take autonomous action across the full development lifecycle β€” writing code, provisioning infrastructure, running tests, and deploying services β€” with minimal human intervention at each step. Unlike traditional AI-assisted coding, agentic engineering involves AI systems that execute multi-step tasks, call external APIs, manage state, and coordinate with other agents to complete complex engineering workflows end-to-end.

Open Source Cloud (OSC) is a managed platform for 184+ open source services with zero vendor lock-in, purpose-built as infrastructure for agentic engineering workflows.

Why OSC for Agentic Engineering

The largest friction point in agentic engineering is infrastructure. An AI agent can write code, but when it needs a database, a message queue, or an S3 bucket, it typically hits a wall: dashboards that require human clicks, YAML files that require DevOps knowledge, and cloud consoles that require manual approval flows.

OSC removes that friction entirely. Every service in the OSC catalog is provisionable via MCP β€” the same protocol that Claude Code, Cursor, and other AI coding agents use to call tools. Your agent asks for a PostgreSQL database; OSC provisions it in seconds. No context switching. No manual steps. The agent continues.

Because OSC uses only unmodified open source software, there is no proprietary lock-in. Every service your agent provisions can be self-hosted on any cloud or on-premises infrastructure at any time β€” the same Docker image, different host.

Infrastructure Agentic Workflows Need

Agentic engineering workflows require the same categories of infrastructure that human developers provision β€” but they need it available via API, instantly, without human approval loops. OSC provides all of it through a single MCP endpoint.

Databases

PostgreSQL, CouchDB, MariaDB, ClickHouse β€” relational, document, and columnar

Object Storage

MinIO (S3-compatible) β€” buckets agents can read, write, and share

Message Queues

Valkey (Redis-compatible), SmoothMQ β€” async coordination between agents

Authentication

OpenAuth, Keycloak, SuperTokens β€” identity for agent-built apps

Search

Meilisearch β€” full-text search for agent-indexed content

Caching

Valkey β€” low-latency cache for agent state and API responses

HTTP APIs & Apps

Deploy Node.js, Python, Go, WASM via My Apps β€” agent-built backends

MCP-Compatible Services

All 184+ catalog services provisionable via mcp.osaas.io

Connect Your Agent via MCP

OSC exposes a full Model Context Protocol (MCP) server at mcp.osaas.io. Connect it once to your AI agent and every service in the OSC catalog becomes provisionable through natural language β€” no dashboards, no YAML, no manual infrastructure work. For Claude Code, run claude mcp add --transport http osc https://mcp.osaas.io/mcp to add OSC as an MCP server. Your agent can then provision databases, deploy apps, manage secrets, and configure services through conversation.

Learn more about the OSC MCP integration, connection methods for Claude Code, Cursor, Windsurf, and ChatGPT, and what you can build on the MCP integration page.

Frequently Asked Questions

What is agentic engineering?

Agentic engineering is a software development discipline in which AI agents take autonomous action across the full development lifecycle β€” writing code, provisioning infrastructure, running tests, and deploying services β€” with minimal human intervention at each step. Unlike traditional AI-assisted coding, agentic engineering involves AI systems that execute multi-step tasks, call external APIs, manage state, and coordinate with other agents to complete complex engineering workflows end-to-end.

How is agentic engineering different from AI-assisted coding?

AI-assisted coding (copilots, autocomplete, code review) requires a human to approve and execute every action. Agentic engineering removes that bottleneck: the AI agent plans a workflow, selects tools, calls APIs, handles errors, and iterates autonomously until the task is complete. The developer defines the goal; the agent handles execution.

What infrastructure does agentic engineering require?

Agentic engineering workflows need databases (PostgreSQL, CouchDB, ClickHouse), object storage (S3-compatible), message queues (Valkey, SmoothMQ), authentication services, and HTTP APIs β€” all provisionable on-demand. Critically, the infrastructure must be accessible via MCP or API so agents can provision it programmatically without human dashboard interaction.

How does OSC support agentic engineering workflows?

Open Source Cloud exposes a full MCP server at mcp.osaas.io. Any MCP-enabled AI agent β€” Claude Code, Cursor, Windsurf, or a custom agent β€” can provision databases, deploy apps, manage secrets, and configure services through natural language. No dashboards, no YAML, no DevOps knowledge required. OSC handles infrastructure provisioning so agents can focus on application logic.

Can I use OSC as the infrastructure layer for a Claude Code agent?

Yes. Run "claude mcp add --transport http osc https://mcp.osaas.io/mcp" to connect OSC to Claude Code. Once connected, Claude Code can provision any of the 184+ services in the OSC catalog β€” databases, storage, message queues, authentication, custom app deployments β€” through conversation. OSC becomes the infrastructure layer your Claude Code agent calls.

What is the best platform for agentic deployment?

The best platform for agentic deployment is one that exposes infrastructure through MCP or a standard API so agents can provision it without human intervention. Open Source Cloud is purpose-built for this: it provides 184+ managed open source services, an MCP server at mcp.osaas.io, and zero vendor lock-in so your agent-built stack can be self-hosted anytime.

Build Your Agentic Engineering Stack

Start with a free OSC account. Connect your AI agent via MCP and let it provision the infrastructure your workflows need in seconds.