Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Descripción del creador (original en inglés)
Validate BGP and routing changes in a real containerlab lab: pass/fail verdict with evidence.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"netdryrun": {
"command": "uvx",
"args": [
"netdryrun",
"mcp"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add netdryrun -- uvx netdryrun mcpPégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"netdryrun": {
"command": "uvx",
"args": [
"netdryrun",
"mcp"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"netdryrun": {
"type": "stdio",
"command": "uvx",
"args": [
"netdryrun",
"mcp"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 6 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub netdryrun, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (0.4.0) llegó al registro hace 6 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv) en tu computadora.
En la misma categoría: Spec Driven Development, Remote Desktop Commander, AI Deprecations
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
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.
AI model shutdown dates, replacements, change feed and webhook alerts for 8 providers.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
Test network changes before they touch production.
Netdryrun is an open-source (Apache-2.0) tool that dry-runs network changes in a real containerlab lab and returns a pass/fail verdict with evidence. It runs as a CLI, a GitHub Action, and an MCP server for AI agents.
Software teams don't ship code without running its tests. Network changes deserve the same step: run the change in a real lab, check how the network behaves, and ship only on a pass. Netdryrun makes that one command, one CI step, or one tool call for an AI agent.
Already have a containerlab lab? [Add Netdryrun to it in 10 minutes](https://netdryrun.com/guides/your-lab/): record its steady state, add one guard, run it on every pull request.
Netdryrun™ boots your topology as a real virtual network (containerlab), applies your configs, and checks how the network actually *behaves*: BGP sessions, prefix counts, routes, reachability. It catches the mistakes your checks describe, such as a route leak, before the change reaches production, and leaves the commands and raw output for a reviewer to inspect.
$ netdryrun run examples/frr-bgp-broken
Deploying lab ndr-frr-broken (3 nodes)... [PASS] r1: BGP session to 10.0.12.2 is established -- state is established (6.3s) [PASS] r1: ping 192.168.3.1 from 192.168.1.1 expects success -- 3/3 replies (2.3s) ... (3 more passing checks trimmed) [FAIL] r1: route 0.0.0.0/0 via bgp is absent -- unexpectedly present via bgp (not selected) (0.1s) FAILED: 5 passed, 1 failed (6 checks)
That run caught a leaked default route that was *received but not selected*. Ping and session checks alone would miss this example: every session is up and every address answers. (A static analyzer such as Batfish also catches this particular leak; the Batfish page shows one that it misses and a lab catches.)
Status: v0.4.0. Runs on Linux and WSL2, with drivers for FRR, Nokia SR Linux, SONiC (docker-sonic-vs), Arista EOS (cEOS, bring your own image) and Juniper cJunosEvolved (beta, bring your own image). On the verdict corpus v1 (30 realistic BGP changes: 19 harmful, 11 safe), Netdryrun judged 24/30 correctly, ping-only checks 20/30 and all-sessions-up checks 15/30. Netdryrun approved 5 of the 19 harmful changes (ping-only checks: 10 of 19) and blocked 1 of the 11 safe ones. On v2 (18 cases written after v1 to target v1's misses): Netdryrun 16 of 17 deterministic cases correct, ping-only 9/17, all-sessions-up 7/17; case 18 is nondeterministic in this lab and excluded from the score (listed with its reruns). Expected verdicts were committed before any run, on one FRR topology: a comparison of testing methods, not a production reliability estimate. Method, every miss and a one-command rerun are on the corpus page. Provenance: both ran on Netdryrun 0.3.1.
The codespace comes with Docker, containerlab and Netdryrun already installed. When the terminal shows Ready, run:
bash examples/agent-demo/demo.sh
A route-leaking change is rejected, then the fix passes every check. It uses your GitHub account's free Codespaces hours (2-core machine). Details.
Requirements: Linux or WSL2, Docker, containerlab, Python 3.10+. On Ubuntu 24.04 and Debian 12 a plain pip install outside a virtualenv is refused ("externally managed environment"), so use pipx: sudo apt install pipx && pipx ensurepath, then open a new terminal. uv tool install netdryrun, or pip install netdryrun inside an activated virtualenv, work too.
pipx install netdryrun
git clone https://github.com/netdryrun/Netdryrun netdryrun && cd netdryrun netdryrun run examples/frr-bgp # 3 FRR routers, should pass netdryrun run examples/srl-frr # SR Linux + FRR, should pass netdryrun run examples/frr-bgp-broken # a bad change, should fail
netdryrun record my-lab/topology.clab.yml --deploy # snapshot today's behavior into my-lab/netdryrun.yml
netdryrun run my-lab # re-run the checks in my-lab/netdryrun.yml
record writes checks for every established BGP session, a prefix-count range for each (today's count up to 20% more, at least 2), guards against a default route or a link subnet arriving via BGP, and up to 50 BGP routes per node. A session that is down today isn't recorded.
Advisory (0.3.3 and 0.4.0): that range lets a leak of one or two extra prefixes from a neighbor pass. Until 0.4.1, record with
--exact-prefixesand addpresent: falsechecks for prefixes that must never arrive. Advisory. Review it (remove what is allowed to change, add negative checks such aspresent: false), commit it, and every future change runs against it, locally or in CI. A pass means those checks passed, nothing more.
lab: topology.clab.yml # your containerlab topology
timeout: 90 # seconds a positive check may wait for convergence
checks:
Failure scenarios break something, check the network still behaves, then restore it. They can take links down, or (from 0.3.1) make an FRR neighbor announce routes it shouldn't, to prove a max-prefix limit or an import filter actually holds:
scenarios:
Every check also accepts name, timeout and vrf. Ping accepts expect: failure and count. Drivers are detected from the topology; override them with nodes: {r1: {driver: frr}}. Nodes that are configured after boot (SONiC) take setup commands: nodes: {sonic1: {setup: [...]}}.
| Check | FRR | SR Linux | Arista EOS (cEOS) | SONiC (VS) |
|---|---|---|---|---|
bgp_session | ✅ | ✅ | ✅ | ✅ |
bgp_prefixes (accepted = received minus rejected by policy) | ✅ | ✅ | ✅ | ✅ |
route present / absent | ✅ | ✅ | ✅ | ✅ |
bgp_route best-path attributes: communities (standard, large, well-known), AS path (exact or regex), local preference, MED, next hop | ✅ | ✅ | ✅ | ✅ |
ping success / failure | ✅ | ✅ | ✅ | ✅ |
| How it is tested | Live lab in CI on every push | Live lab in CI on every push | Parsers tested against output captured from live labs; no live lab in CI | Parsers tested against output captured from live labs; no live lab in CI |
| Command | What it does |
|---|---|
netdryrun run [path] | Deploy the lab, run the checks, destroy the lab. Add --keep to leave it up for debugging |
netdryrun check [path] | Run the checks against a lab that is already running |
netdryrun validate [path] | Validate netdryrun.yml and its topology without running anything |
netdryrun record topology.clab.yml | Snapshot a known-good lab into a netdryrun.yml baseline, so you don't write checks by hand |
Reports: --json FILE (full evidence), --markdown FILE, --junit FILE. Under GitHub Actions, a summary is appended to the job page automatically. Exit codes: 0 passed, 1 a check failed, 2 no verdict (config or lab error, a fault that did not take effect, or an internal error; add --debug for the traceback), 3 inconclusive (the lab never reached a testable state, so the run says nothing about the change), 130/143/129 interrupted by SIGINT/SIGTERM/SIGHUP after cleaning up the lab.
name: Network dry run
on: pull_request jobs: dryrun: runs-on: ubuntu-latest steps:
The action installs containerlab, runs the checks, uploads the JSON and JUnit reports as an artifact, and fails the job if any check fails. Outputs: status, passed, failed, inconclusive-reason.
Listed in the official MCP Registry (io.github.netdryrun/netdryrun) and on Glama; the agent skill is also on Smithery.
AI can propose network changes. Netdryrun verifies the outcome. Agents: read [AG
Solo se muestra el principio; lee el resto en el repo