Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Validates AI infra code on real VMs. Self-corrects until it works. No containers, no sandboxes.
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Works in Claude on the web, desktop and mobile:
https://antrieb.sh/mcpRun this in your terminal
claude mcp add --transport http antrieb https://antrieb.sh/mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"antrieb": {
"url": "https://antrieb.sh/mcp"
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"antrieb": {
"type": "http",
"url": "https://antrieb.sh/mcp"
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
ChatGPT connects only to servers on the internet:
https://antrieb.sh/mcpMenu names can differ slightly by plan and over time.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
We have not read this server’s tool list yet; we check endpoints in rotation.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The registry name was verified against the domain antrieb.sh (the registry checks domain ownership)
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
Not checked yet; we check endpoints in rotation
Not checked yet; we check endpoints in rotation
Not checked yet; we read the tool list when we check the endpoint
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.
The GitHub repo last changed –, and the latest version (1.0.1) reached the registry 7 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.
In the same category: Spec Driven Development, Remote Desktop Commander, Asset Notation
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Read and maintain an Asset Notation file on disk: net worth, holdings, valuations, CSV import.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
Instant disposable clusters for LLM-generated networks and infra.
Say an LLM writes a VyOS NAT config, an OpenWrt firewall rule set, or a bash script to harden a CentOS cluster. Where do you run it before it touches your environment? Antrieb gives the LLM a disposable multi-node cluster, with real VMs and real networking, to try what it generates. Break it, quickly reprovision, try again. No cleanup.
Same OS and appliances your LLM-generated code will target in production: CentOS Stream, Ubuntu, Debian, Alma, Alpine, VyOS, OPNsense, SONiC, OpenWrt. Multi-network topologies with per-NIC assignment. Not a container, not a microVM, not some unknown Linux — the same kernels and packages your real fleet runs.
Root access, private networking, passwordless SSH between nodes. Ten minutes per cluster. Clean slate every time. Instant clusters that change the economics of being wrong for LLMs.
Antrieb is a remote MCP server. Nothing to install. Add it to your config and start provisioning.
With web-based AI clients, add Antrieb as a custom connector.
In claude.ai: go to Settings → Connectors, click Add custom connector. Enter:
Antriebhttps://antrieb.sh/mcpClick Add, then Connect and sign in. Back in your chat, try something like:
*Create a 3-node Kubernetes cluster, with node1 running both as control-plane and worker, and node2/node3 as pure workers. Install nginx with 3 pods and pod anti-affinity.*
Walkthrough video: https://youtu.be/8nts8ol-yeA
Get a free API key at antrieb.sh/dash, then add this to your MCP client config (e.g. .mcp.json for Claude Desktop):
Put this JSON in the current folder in a file called .mcp.json. Claude Code will find it automatically.
{
"mcpServers": { "antrieb": { "type": "http", "url": "https://antrieb.sh/mcp", "headers": { "Authorization": "Bearer ant_YOUR_API_KEY" } } } }
#### Codex
Put this TOML content in ./.codex/config.toml. Then set the ANTRIEB_TOKEN environment variable with your API key before launching Codex.
[mcp_servers.antrieb]
url = "https://antrieb.sh/mcp" bearer_token_env_var = "ANTRIEB_TOKEN"
No local install, no dependencies, no Docker.
Your LLM controls real VMs through 5 tools:
1. provision → Spin up a cluster (sub-second per VM, declare custom networks and NICs)
The LLM drives the entire workflow: provision a cluster, install software command by command, verify each step, and iterate until it works. Antrieb provides the infrastructure; the LLM provides the intelligence.
You: provision 3 ubuntu nodes and install nginx on all nodes
LLM: provision(cluster: ["ubuntu24.04 x3"]) → { session_id: "abc12", nodes: ["node1", "node2", "node3"], provision_time_ms: 720 }
LLM: exec(session_id: "abc12", node: "node1", command: "apt-get update && apt-get install -y nginx") → { exit_code: 0, stdout: "..." }
LLM: exec(session_id: "abc12", node: "node1", command: "systemctl start nginx && curl -s localhost") → { exit_code: 0, stdout: " Welcome to nginx... " }
LLM: save(type: "image", session_id: "abc12", node: "node1", name: "my-nginx", commands: [...]) → { ani: "antrieb:my-nginx:v1" }
LLM: delete(type: "cluster", name: "abc12") → { success: true }
| ANI | Description |
|---|---|
ubuntu24.04 | Ubuntu 24.04 LTS: apt, bash, Python 3, curl, wget, jq |
almalinux9 | AlmaLinux 9 (RHEL-compatible): dnf, bash, Python 3 |
centos-stream10 | CentOS Stream 10: dnf, bash, Python 3 |
debian13 | Debian 13: apt, bash, Python 3, curl, wget, jq |
alpine | Alpine Linux 3.23: apk, minimal, musl libc |
sonic | SONiC: open-source network OS for data-center switches |
vyos | VyOS: Linux-based router / firewall with a unified CLI |
openwrt | OpenWrt 25.12: Linux-based firmware with UCI configuration |
opnsense | OPNsense: FreeBSD-based firewall / router with web UI |
Stack images are custom images created by enriching the base images with additional packages.
| ANI | Description |
|---|---|
terraform-aws | Terraform with real AWS (free-tier, Antrieb's credentials, Vault-brokered STS) |
ansible-controller | Ansible control node with collections |
podman | Podman, Buildah, Skopeo (rootless, Docker-API-compatible) |
mongodb | MongoDB server image for database provisioning and integration tests |
postgresql | PostgreSQL server image for SQL database tests |
vault | HashiCorp Vault image for secrets workflows and Terraform-backed credentials |
mariadb | MariaDB server image for MySQL-compatible database tests |
nginx | NGINX image for web server and reverse-proxy scenarios |
helm-k3s | K3s with Helm for lightweight Kubernetes scenarios |
asterisk-pbx | Asterisk PBX image for SIP and telephony scenarios |
Use search to discover all available images with full descriptions, or just specify a distro name and Antrieb picks the right one.
Networking is a first-class input to provision, not an afterthought. Every cluster is L2-isolated from every other cluster (even ones you own), with hostname resolution, passwordless SSH between its own nodes, and cluster-scoped env vars auto-injected into every exec call. What *varies* between runs is how nodes are wired and controlled by the optional networks and nics parameters on provision.
There are two modes: the default network (flat, one-subnet, internet-reachable) and declared networks (first-class multi-subnet, multi-NIC topologies).
node1, node2, node3 in /etc/hosts on every node.ssh node2 hostname just works.NODE_NAME, NODE_INDEX, NODE_IP, CLUSTER_HOSTS (multiline IP NAME — drop-in for /etc/hosts), CLUSTER_SSH_PUBKEY, CLUSTER_SSH_PRIVKEY.LLM: exec(node: "node1", command: "ssh node2 hostname")
→ { stdout: "node2" }
networks / nics are omitted)LLM: provision(cluster: ["ubuntu24.04 x3"])
You get:
/24 network named default, one NIC per node, DHCP-assigned IPs.Use this whenever the *network* isn't what you're testing — application-level work, distro-specific configuration, Ansible playbooks, CI pipelines, Kubernetes-on-three-ubuntus.
Pass networks and nics when the topology itself is the thing under test: routers, firewalls, DMZs, isolated back-end subnets, dual-homed nodes, BGP meshes.
LLM: provision(
cluster: ["vyos", "ubuntu24.04", "ubuntu24.04"], networks: [ { name: "wan", egress: true }, { name: "lan", cidr: "10.10.1.0/24", egress: false } ], nics: { node1: [{ net: "wan" }, { net: "lan" }], // vyos: dual-homed router node2: [{ net: "lan" }], // ubuntu backend node3: [{ net: "lan" }] // ubuntu backend } )
Contract:
/24. CIDRs are auto-allocated when omitted; only /24 is supported.nics. becomes eth0, eth1, ... in the listed order..254 (or DHCP-client) — assigning .1 to a VM causes ARP flip-flop.This unlocks serious networking work: VyOS / OPNsense firewalls with WAN/LAN zones, SONiC as an L2 switch or L3 router, OpenWrt with its fw3 zone model, nginx behind a reverse-proxy LAN, BGP peering over /31 transit links, hairpin NAT, DNAT port-forwards. Full walkthroughs for each pattern live in the @antrieb/* runbook library.
Reusable topologies should be captured in runbooks. Networks are declared inline during provision; if the same topology matters across scenarios, save the topology, commands, and verification steps together as a runbook.
The default antrieb/* runbook library includes verified scenarios such as:
Runbooks are written as executable proofs: topology, commands, expected packet behavior, and verification steps using tools like tcpdump, route tables, conntrack, BGP/OSPF state, DHCP traces, VPN handshakes, and failover tests.
Runbooks are the way to preserve non-trivial multi-node scenarios, capturing even little gotchas that may be too small to blog about. They're markdown documents with structure the LLM can execute:
## Topology required — cluster shape this applies to (images, networks, NICs)## Variables — placeholders like callers substitute at apply time## Steps — numbered; prose explains *why*, fenced shell blocks are the actual commands, each annotated with the node it targets## Verify — how to confirm successSave one with save(type: "runbook", session_id: "...", name: "...", body: "...markdown..."). The session_id must point to a session whose exec history demonstrates the runbook. Fetch the body with search(type: "runbook", fq_name: "namespace/name").
Runbooks complement images: an image captures installed state (packages, configs baked into a qcow2). A runbook captures a workflow (the ordered, multi-node actions that produce a working system). Prefer runbooks for anything with more than one node, because a single image can't express coordination between VMs.
Everything you save lives in your org's namespace; the antrieb/* namespace is read-only defaults.
Save any configured node as a reusable image:
execsave(type: "image", ...) with the list of successful commandsbuild-image.sh, startup.sh, and a descriptionprovision callsOnly the beginning is shown; read the rest in the repo