Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Descripción del creador (original en inglés)
Cost-parity bench for agent loops: $/success and time across model mixes, with verifiable receipts.
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.
ANTHROPIC_API_KEY, OPENAI_API_KEYLos valores marcados como secretos son llaves de tu cuenta. Nunca los compartas ni los pegues en un chat.
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": {
"plzebo": {
"command": "npx",
"args": [
"-y",
"plzebo"
],
"env": {
"ANTHROPIC_API_KEY": "your-value",
"OPENAI_API_KEY": "your-value"
}
}
}
}Ejecuta esto en tu terminal
claude mcp add plzebo --env ANTHROPIC_API_KEY=your-value --env OPENAI_API_KEY=your-value -- npx -y plzeboCompleta los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"plzebo": {
"command": "npx",
"args": [
"-y",
"plzebo"
],
"env": {
"ANTHROPIC_API_KEY": "your-value",
"OPENAI_API_KEY": "your-value"
}
}
}
}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": {
"plzebo": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"plzebo"
],
"env": {
"ANTHROPIC_API_KEY": "your-value",
"OPENAI_API_KEY": "your-value"
}
}
}
}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 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub wkoverfield, 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.
Debes completar: ANTHROPIC_API_KEY, OPENAI_API_KEY
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 (0.2.0) llegó al registro hace 3 meses.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.
En la misma categoría: Spec Driven Development, Remote Desktop Commander, OpenTakeoff
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.
Construction takeoff for AI agents: load plans, set scale, measure, count, export with provenance.
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.
Cost-parity bench for agent loops. Point it at two or more ways of getting the same task done (a cheaper model mix, a different setup, a tool on vs off) and it measures which one delivers the outcome for less, in dollars and in minutes, and whether the gap is real or noise. Runs locally, on your own keys or your own subscription. An agent can call it on itself over MCP.
The headline metric is cost per successful outcome: total metered spend divided by successes, compared across arms with a 95% confidence interval. Time per successful outcome is reported beside it. When the data cannot support a claim, plzebo says so instead of making it.
claude-* call to each arm's model.sk-placebo-...) and a redirected base URL; the gateway swaps in the real key upstream and records provider-reported token usage per call. A call that bypasses the gateway fails at the provider instead of billing invisibly, and a trial with zero metered calls is flagged, never compared.plzebo verify receipt.json recomputes every derived number from the raw rows and reports any divergence.Node 22.6 or later (the CLI runs its TypeScript sources through Node type stripping; the launcher supplies the flag on versions that need it). Git, plus whatever your arms and oracle need (for the examples here: python3).
npx plzebo run spec.yaml --estimate # prices the run from prior receipts; spends nothing
npx plzebo run spec.yaml # runs the experiment npx plzebo verify # recompute a receipt's claims from its raw rows
A spec:
name: sonnet-vs-opus
fixture: repo: ./my-fixture-repo # a git repo; every trial gets a fresh clone ref: main task: "Make the failing tests in this repo pass. Do not edit the tests." arms: sonnet: cmd: claude --print "$PLZEBO_TASK" --dangerously-skip-permissions --strict-mcp-config --mcp-config '{"mcpServers":{}}' --model claude-sonnet-5 auth: passthrough # runs on your logged-in Claude subscription rewrite: claude-*: claude-sonnet-5 # pin every call this arm makes, including auxiliary ones opus: cmd: claude --print "$PLZEBO_TASK" --dangerously-skip-permissions --strict-mcp-config --mcp-config '{"mcpServers":{}}' --model claude-opus-4-7 auth: passthrough rewrite: claude-*: claude-opus-4-7 baseline: opus oracle: cmd: [python3, -m, unittest, discover, -s, tests, -t, .] k: 3 trialTimeoutMs: 600000 budgetUsd: 30 # hard kill switch enforced at the gateway
Every run prints its cost estimate before the first trial. A run without a budget is refused. Start with a small K: the report on an inconclusive run prints the exact K that would resolve it and the estimated cost, and plzebo extend --to-k K reuses the trials you already paid for. A receipt can be extended once, and the extension is disclosed inside it.
auth: placebo (default): you export ANTHROPIC_API_KEY or OPENAI_API_KEY; arms only ever see placebo keys. Strongest metering guarantee: a bypassing call fails loudly.auth: passthrough: the arm uses its own login. No API credits are spent; USD is imputed from metered tokens at list rates and the receipt discloses this. Tokens are the ground truth either way. Verified for Claude Code, which honors ANTHROPIC_BASE_URL under subscription auth. Codex under ChatGPT auth routes to its own backend and ignores OPENAI_BASE_URL, so subscription-authed Codex is unmeterable; run Codex arms in API-key mode via the codex-cli template instead.Two caveats for passthrough arms. A trial that bypasses the meter is excluded rather than falsely counted, but the tokens it consumed upstream are real; the receipt cannot see them. And a personal login carries personal agent configuration: instructions, hooks, and memory files travel with it, which can inflate costs and, for agents that act on standing instructions, cause writes outside the trial workspace. Prefer isolated-config templates when comparing loops rather than your own setup.
Every cost node in a receipt records two models: role, the model the loop REQUESTED, and model, what the arm's rewrite rules resolved it to. A loop that requests different models for different jobs (a main session on one model, subagents on another) therefore encodes its role structure into the receipt, and arms that share the same command can bind those roles differently through rewrites alone:
arms:
mixed: cmd: sh scripts/arms/subagent-mix.sh # opus main session + a worker agent definition requesting sonnet auth: passthrough rewrite: claude-opus-*: claude-opus-4-7 # orchestrator stays opus claude-sonnet-*: claude-sonnet-5 # workers stay sonnet claude-*: claude-opus-4-7 # catch-all LAST: wildcard rules match in order after exact keys all_opus: cmd: sh scripts/arms/subagent-mix.sh # byte-identical loop; only the mapping differs auth: passthrough rewrite: claude-*: claude-opus-4-7
The packaged scripts/arms/subagent-mix.sh shows the Claude Code shape: a headless session with an inline --agents definition whose worker requests a different model than the main session. Adapt the agent prompt and models to your task.
A model-mix comparison is only valid when the loop actually delegated: a trial whose cost tree has no worker-role calls measured a solo run, not a mix.
npx plzebo fidelity <receipt.json|run-dir> # per-trial requested -> resolved counts
npx plzebo fidelity --worker "claude-haiku-*"
fidelity exits 1 if any completed trial never made a worker-role call, and prints each trial's call counts, tokens, and imputed spend grouped by requested and resolved model, so the mix an arm claims is checkable from its receipt.
The gateway speaks two wire formats: Anthropic and OpenAI-compatible, which covers most open-weight serving (Ollama, vLLM, OpenRouter, Together, and similar). Arms can override providers individually:
arms:
local-qwen: cmd: my-loop --task "$PLZEBO_TASK" upstreams: openai: http://127.0.0.1:11434 # any OpenAI-compatible server gpt: cmd: my-loop --task "$PLZEBO_TASK" keysFrom: openai: OPENAI_API_KEY # env var NAME; specs never contain key values
Constraint: plzebo can only meter loops that authenticate with a key or token and honor a redirectable base URL (ANTHROPIC_BASE_URL / OPENAI_BASE_URL).
npx plzebo-mcp serves four tools on stdio: measure_start, measure_extend, measure_status, and measure_result. Starting a measurement is two-phase: the first call validates the request and returns a cost estimate plus a one-time confirm token while spending nothing; only a second call presenting that token runs trials. A budget is mandatory, and MCP arms come only from named templates (claude-cli, claude-subscription, codex-cli), never raw shell. Job state and receipts persist under .plzebo/, so verdicts survive the session that produced them.
A receipt is a single-task result under a stated model mapping. It is not a model capability ranking and does not generalize beyond its fixture; the estimand text inside the receipt says exactly this. USD figures on passthrough arms are imputed at pricing-table rates from metered tokens, not billed spend, and the pricing table version travels in the receipt so the numbers stay recomputable after prices change.
MIT