Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Descripción del creador (original en inglés)
Wraps any MCP server: identical write-tool calls run once, and every tool call is audit-logged.
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.
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Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"agentraas": {
"command": "uvx",
"args": [
"agentraas",
"wrap",
"--"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add agentraas -- uvx agentraas wrap --Este necesita valores en su línea de comandos, así que copia la configuración y complétalos.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"agentraas": {
"command": "uvx",
"args": [
"agentraas",
"wrap",
"--"
]
}
}
}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 necesita valores en su línea de comandos, así que copia la configuración y complétalos.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"agentraas": {
"type": "stdio",
"command": "uvx",
"args": [
"agentraas",
"wrap",
"--"
]
}
}
}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 agentraas, 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 (0.16.0) 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, dotnet-mcp
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.
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MCP server for .NET symbols, XAML, source generators, and restricted workspace edit
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.
The reliability layer for what AI agents do. Every action your agent takes (a charge, an email, a CRM update, a tool call) runs once even when it is retried, can be checked against rules before it runs, and is recorded. This package brings that to your code:
@exactly_once and protect_tool (LangChain/LangGraph, CrewAI): a retry, yours, your framework's or a flaky network's, never becomes a duplicate charge or message. No server needed.agentraas wrap: the same for any MCP server's write tools.agentraas scan: lists which tools in your MCP servers can move money, delete data, run code or send messages, without calling any of them.agentraas chaos: finds the calls in your agent that would double up under retries, before production does.Client: points your calls at an AgentRaaS server for action policies, human approval, spend caps, circuit breaking and an audit trail.Works against any AgentRaaS deployment: self-hosted (./install.sh, free and unlimited on every tier) or AgentRaaS Cloud.
pip install agentraas
Wrap any function that has a side effect (charging a card, sending an email, creating a CRM record) so retries and concurrent duplicates run it exactly once. Nothing to deploy: state lives in a local SQLite file by default, or in your own Redis.
from agentraas.local import exactly_once, RedisStore
@exactly_once() # SQLite file, one machine def charge(customer, amount): return stripe.Charge.create(customer=customer, amount=amount).id
charge("cus_1", 4200) # runs for real charge("cus_1", 4200) # retry: returns the cached id, no second charge
@exactly_once(store=RedisStore("redis://localhost:6379/0"), key=lambda order: order["id"], ttl=3600) async def ship(order): ...
idempotency_key parameter and send it to the provider (e.g. Stripe's Idempotency-Key header). The decorator fills it with the same value on every retry: @exactly_once()
def charge(customer, amount, idempotency_key=None): return stripe.Charge.create(customer=customer, amount=amount, idempotency_key=idempotency_key).id
- A duplicate that arrives while the first call is still running waits for
its result (up to wait=30 seconds, then InFlightError).
RedisStore needs pip install redis.When you want a dashboard, audit trail, human approval or circuit breaking on top, point the same calls at an AgentRaaS server with the Client below.
pip install "agentraas[langchain]", then wrap the tools that have side effects. Works with LangChain agents, create_react_agent and ToolNode.
from agentraas.langchain import protect_tool
tools = [protect_tool(charge_card), protect_tool(send_email), search] agent = create_react_agent(model, tools)
When the model calls a protected tool again with the same arguments, or the graph re-runs the tool node after a crash or retry, the stored result comes back instead of a second charge. Takes the same store=, key= and ttl= options as @exactly_once above (e.g. store=RedisStore(...) for several workers, key=lambda order_id, **_: order_id). Tool results must be JSON-serializable.
pip install "agentraas[crewai]" (CrewAI needs Python 3.10+), then wrap the tools that have side effects, either BaseTool subclasses or @tool functions:
from agentraas.crewai import protect_tool
agent = Agent(role="Billing", goal="...", backstory="...", tools=[protect_tool(ChargeCardTool()), protect_tool(send_email)])
When the agent calls a protected tool again with the same arguments, or a crew is kicked off again after a crash, the stored result comes back instead of a second charge. Same store=, key= and ttl= options as above. The original tool object is left unchanged.
Put agentraas wrap -- in front of an MCP server's command. Everything passes through unchanged, except that an identical call to a write tool (same tool, same arguments) inside the dedup window gets the first call's result back instead of running again. An agent that retries or loops can't send the same email or open the same issue twice. Every tool call is appended to an audit log.
Claude Desktop / Cursor config:
{
"mcpServers": { "github": { "command": "uvx", "args": ["agentraas", "wrap", "--", "npx", "-y", "@modelcontextprotocol/server-github"] } } }
readOnlyHint annotation decides, falling back to names like get_*, list_*, search_*. Override with --dedupe TOOL / --no-dedupe TOOL.isError: true) is not cached, so a retry runs for real.--ttl 600). State lives in ~/.agentraas/mcp-dedup.db, the log in ~/.agentraas/mcp-audit.jsonl (--db, --log)._meta: {"agentraas/deduplicated": true}.agentraas scan # every server in your Claude Desktop, Cursor, Claude Code configs
agentraas scan -- npx -y @modelcontextprotocol/server-github agentraas scan --config .mcp.json --fail-on high # CI: exit 1 on a high-risk tool
Starts each stdio server the way your client does, sends only initialize and tools/list, and sorts the tools: moves money, deletes, runs code, sends (high), writes (medium), reads (low), from their readOnlyHint/destructiveHint annotations and the words in their names. Only scan configs you trust: it runs their commands. --json for machine-readable output. https://agentraas.io/mcp-scan
GitHub Actions:
- uses: agentraas/agentraas/src/scan-action@main
with: config: .mcp.json # or command: "npx -y @modelcontextprotocol/server-github"; fail-on: high | medium | none
agentraas-chaos sits between your code and an API. The first time each distinct write request (POST/PUT/PATCH/DELETE) arrives, it lets the request execute and then drops the response, the network failure that turns a retry into a double charge. Then it reports every action that executed more than once.
pip install agentraas
agentraas-chaos --mock -- python my_agent.py
agentraas-chaos --upstream https://api.stripe.com -- pytest
Your command gets AGENTRAAS_CHAOS_URL (e.g. http://127.0.0.1:8787); use it as the API base URL. Without a command it runs until Ctrl-C, so you can point an n8n workflow or any other tool at it by hand.
agentraas-chaos: 6 write requests, 3 responses dropped after execution
DUPLICATES: 1 action(s) executed more than once
2x POST /v1/charges (body sha256 623f14d1b00d) ... Protected by an idempotency key: 2 retries
It exits with code 1 when it finds a duplicate, so it can fail CI. --fault error-after-commit returns a 502 instead of dropping the connection. A retry that repeats an Idempotency-Key it has already seen is counted as protected, not executed again.
In GitHub Actions:
- uses: actions/setup-python@v5
with: { python-version: "3.12" }
agentraas applyDescribe a server's dedup rules, validation rules, action policies and spend caps in YAML, review them like code, and apply them from CI:
pip install "agentraas[apply]"
# agentraas.yaml
apiVersion: agentraas.io/v1alpha1 kind: DedupRule metadata: {name: charge-once, org: org_acme} spec: {service: stripe, action: charges.create, fields: [customer, amount], ttlSeconds: 300}
apiVersion: agentraas.io/v1alpha1 kind: SpendCap metadata: {org: org_acme} spec: {service: stripe, action: refunds.create, window: day, maxCalls: 100, onExceed: block}
export AGENTRAAS_URL=https://agentraas.example.com AGENTRAAS_EMAIL=ci@acme.com AGENTRAAS_PASSWORD=...
agentraas apply -f agentraas.yaml --dry-run # print the plan agentraas apply -f agentraas.yaml # create what's missing, replace what changed agentraas apply -f agentraas.yaml --prune # also delete rules the file doesn't list
Kinds: DedupRule, ValidationRule, ActionPolicy, SpendCap. Spec keys are the API's fields in camelCase. Running it twice changes nothing.
agentraas tunnel prints a public URL and replays every request sent to it against a local port, so you can point Stripe, GitHub or n8n webhooks at code you haven't deployed. Needs a free AgentRaaS account (an agent API key).
pip install "agentraas[tunnel]"
agentraas tunnel --port 3000 --org org_acme --agent agent_1 --key ar_live_...
One tunnel per org, 2-hour sessions, 30-second local response timeout.
agentraas callEvery command also runs under the short name agtrs. call sends one action through an AgentRaaS server and prints the answer as JSON: the same dedup, policies, approvals and audit as the Client. Handy for scripts and for checking a rule by hand.
export AGENTRAAS_KEY=ar_live_... AGENTRAAS_ORG=org_acme AGENTRAAS_AGENT=agent_1
export AGENTRAAS_URL=https://agentraas.io # default http://localhost:13000 agtrs call stripe charge.create '{"amount": 4999, "currency": "usd"}' echo '{"text": "hi"}' | agtrs call slack message.post -
--key, --org, --agent, --url and --idempotency-key override the environment. A rejected call prints the error and its hints and exits 1.
The same list as the dashboard's Waiting for approval, for any org you can write to. Logs in like apply (AGENTRAAS_EMAIL / AGENTRAAS_PASSWORD against AGENTRAAS_URL, default https://agentraas.io).
agtrs approvals # req id, service, action, agent, payload
agtrs approve req_abc123 # runs the call; asks first (--yes to skip) agtrs deny req_abc123
approve exits 1 if the call ran and failed (it is then in Failed requests). Without a terminal it refuses unless --yes is passed, so a script never approves by accident.
Every call in the orgs you belong to, newest first, with the same login as approvals:
agtrs audit # last 50: time, status, service action, agent, org, duration, req id, error
agtrs audit -n 200 --json # adds run/step ids, dedup hash, redacted payload preview (max 1,000) agtrs audit --csv > audit.csv # the dashboard's CSV export (newest 10,000)
Calls that failed and were kept (the dashboard's Failed requests), with the same login as approvals:
agtrs dlq # id, time, service action, agent, org, req id, error
agtrs dlq replay 42 # sends the call again with the same idempotency key; asks first (--yes to skip) agtrs dlq dismiss 42 # drop it without sending
replay exits 1 if the service fails again; the entry stays in the list.
agtrs rules prints the rules alr
Solo se muestra el principio; lee el resto en el repo