Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Descripción del creador (original en inglés)
Offline TrustLint checks: EU AI Act Article 5, Article 50, GPAI, plus GDPR and HIPAA.
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": {
"complyedge": {
"command": "npx",
"args": [
"-y",
"@complyedge/mcp"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add complyedge -- npx -y @complyedge/mcpPégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"complyedge": {
"command": "npx",
"args": [
"-y",
"@complyedge/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": {
"complyedge": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@complyedge/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 ComplyEdge, 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 (0.2.22) llegó al registro hace 7 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv), Node.js 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.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
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.
Prove what your AI decided, without keeping what it saw. Every request and answer is checked against open EU AI Act rules that cite the law: one record per decision, never a copy of the text.
complyedge is the Python client for the hosted ComplyEdge runtime API. It enforces policy decisions in your application and records the resulting evidence trail. For an offline command-line linter with no API key, use TrustLint instead.
pip install complyedge
from complyedge import compliance_check
@compliance_check( jurisdiction="EU", agent_id="my-agent", decision_context={ # what only you know, for an ADCR-complete record "deciding_system": {"version": "gpt-5.4-2026-08-01"}, "purpose_ref": "purpose:support-replies", "data_categories": ["contact"], }, ) def my_agent(prompt): return llm.generate(prompt) # every input and output checked
That's it. Every input and output is checked against the EU AI Act rule set (Article 5, Article 50, GPAI). Every check gets a record with an event_id, the rules that fired (if any), a timestamp and a keyed hash of the text. A block by a rule also gets its legal citation. On a paid plan the injection check can also block when the month's model budget covers it, and that block names the law. A wider-review block does not cite an article. If that review is on and clears every hit, the request is allowed. decision_context is optional: without it every check still runs and is recorded, but the record does not meet ADCR class Record (see Tell the record what only you know). With the default fail mode, open, an API outage lets traffic through unchecked and unrecorded; set COMPLYEDGE_FAIL_MODE=closed, or pass config=ComplianceConfig(fail_mode="closed"), to raise ComplianceUnavailableError instead. Without an API key the decorator always runs the function unchecked.
Classifiers (eu-ai-act-* MCPs) score the *system*. ComplyEdge checks and records *this* prompt or output. Article 50 here is unlabeled or deceptive use, not C2PA watermarking.
Each line is an alternative; pick the one you need.
pip install complyedge # this SDK: hosted checks and the decorator
pip install 'complyedge[mcp]' # plus the MCP server: complyedge-mcp pip install 'complyedge[agents]' # plus the OpenAI Agents guardrail pip install trustlint # offline linter CLI, separate package npx -y @complyedge/mcp # the MCP server on Node, no Python claude mcp add complyedge -- npx -y @complyedge/mcp # add the Node MCP server to Claude Code
OpenAI Agents extra (hosted path; needs COMPLYEDGE_API_KEY): from complyedge.agents import create_compliance_guardrail
GitHub Action: uses: complyedge/trustlint-action@v1
The decorator reads your API key from the COMPLYEDGE_API_KEY environment variable by default. Pass api_key_env="MY_VAR" to use a different one.
jurisdiction is where the end user is, not where your company is based: the EU AI Act applies when an AI system's output is used in the EU, wherever the provider or deployer is established (Art. 2(1)(c)). Default: EU.
| Value | What the phrase rules cover |
|---|---|
EU | EU AI Act: Article 5 prohibited practices, plus Article 6 high-risk, Article 50 and GPAI (Articles 51 to 55) rules that fire on text describing a missing control; prompt-injection detection; personal data and secrets (citing GDPR). Any rule that fires blocks the call. |
US, US-* | SEC Regulation FD selective disclosure + prompt-injection detection |
On a paid plan, a clean pass then runs an injection check when the month's model budget covers it, which can block. The wider review runs only when you turn it on and that budget covers it.
HIPAA, COPPA, TCPA, BIPA, CCPA, NYC LL144 and ECPA rules, and the GDPR YAML rules (consent, data minimisation, DPIA, erasure, breach notification, transfers), run offline in TrustLint (pip install trustlint), not on the hosted /v1/check path. The hosted personal data and secrets rules above cite GDPR Articles 5(1)(c) and 32(1).
@compliance_check(jurisdiction="EU", agent_id="hr-screening")
def hr_screening(candidate: str) -> str: return llm.generate(candidate)
Per-rule scoping (e.g. only Article 5) is planned but not yet exposed in the SDK: all rules for the selected jurisdiction run today.
# Development setup
pip install 'complyedge[dev]'
pip install -e ./sdks/python
from complyedge import ComplyEdge
ce = ComplyEdge(api_key="your-key") result = ce.check("AI-generated content", jurisdiction="EU")
if result.allowed: print("Content approved") else: for v in result.violations: print(f"{v.rule_id}: {v.rule_description}") # the rule's legal citation
Every audit record has user_id, user_role and session_id. They are filled only when you send them; leave them out and those columns are blank in your audit export.
# Per call
ce.check(text, user_id="ref_5d81e2c4", user_role="recruiter", session_id="conv_abc")
ce = ComplyEdge(api_key=api_key, user_id="ref_5d81e2c4", user_role="recruiter", session_id=run_id)
@compliance_check(jurisdiction="EU", attribution=lambda: {"user_id": current_user.id, "session_id": request_id}) def answer(prompt: str) -> str: ...
ComplyEdgeClient.check_compliance() and the async client take the same three keyword arguments; they override the same keys in context. Use a stable identifier from your own system, never a name or an email address. user_id and session_id are stored as keyed pseudonyms (p1:...) under your account's own key, not as sent; user_role is stored as sent, so it must name a role, not a person.
Never send a credential in these fields: a login token, session cookie, JWT or API key would sit in every audit record and export. If your session id doubles as a login token, send a hash of it (for example the first 16 hex characters of its SHA-256). ComplyEdge replaces any token- or key-shaped value with redacted: plus a hash before the record is written.
ComplyEdge never stores the prompt or the answer. The record keeps text_hash, a keyed hash (HMAC-SHA-256) of the input under your account's own key, so it cannot be recomputed locally. Keep the event_id next to your own copy of the text, and ask the API when you need to prove the pair:
result = ce.check(text)
app_log.info("chat turn", prompt=text, complyedge_event_id=result.event_id) # your own log
assert ce.verify_input(result.event_id, text) # True only for this exact text
Optional: pass receipt_journal="/var/lib/app/complyedge-receipts.jsonl" to ComplyEdge(...) (or use ReceiptJournal yourself) to append event_id, text_hash, and digests locally after each non-sandbox check. The journal never stores the prompt; your app log still holds the text.
The full walkthrough, including what happens if you delete your copy early: https://complyedge.io/docs/audit-reconciliation.html
result.text_hash_alg is "hmac-sha256-1"; records written before the keyed hash was introduced carry none and hold a plain SHA-256, which verify_input also checks.
The audit record can carry fields ComplyEdge cannot know: the version of your AI system, the purpose of the processing and the categories of personal data the decision used. Pass them as decision_context; they are written to the record as ADCR 0.1.0 fields (https://complyedge.io/producer-profile/). decision_context is optional: without it the check runs and is recorded, but the record does not meet ADCR class Record. When you send it, deciding_system.version, purpose_ref and data_categories ([] when none) are required; every other key is optional. check(), is_safe(), the global check() and is_safe(), check_compliance() and the decorator (a dict, or a zero-argument function read on every call) all take it.
result = ce.check(
text, decision_context={ "deciding_system": {"version": "gpt-5.4-2026-08-01"}, "purpose_ref": "purpose:support-replies", "data_categories": ["contact"], }, )
sandbox=True calls POST /v1/sandbox/check: the same rules, the same tenant settings and the same verdict, but no audit entry, no usage and no count against your plan's daily limit (sandbox calls have their own caps: 60 a minute, 1,000 a day). Use it to test cases before wiring an integration. A sandbox result is never evidence: result.sandbox is True and result.audit_logged is False.
result = ce.check("Score users based on their social behavior", sandbox=True)
print(result.blocked, result.sandbox) # True True
Or the global convenience functions:
from complyedge import is_safe, check
import os
api_key = os.environ["COMPLYEDGE_API_KEY"]
if not is_safe(text, api_key=api_key, jurisdiction="EU"): raise ValueError("Compliance violation")
result = check(text, api_key=api_key, jurisdiction="EU")
Keys are shown once, at creation, and stored as a hash: a lost key cannot be recovered, only replaced. Rotate without downtime, in this order:
COMPLYEDGE_API_KEY or the api_key you pass to the client) and deploy.Compromised key: revoke first (Revoke this key on the card, or Revoke on the row), then rotate. Via the API the same flow is POST /v1/account/api-keys, then DELETE /v1/account/api-keys/{key_id} for the old key.
Your public AI Trust Center and Enforcement Seal show one company name: the one set in the dashboard under Account, Profile. display_name on PATCH /v1/tenant/trust sets the same value, so an API call and the profile never disagree. Email is your sign-in and cannot be changed from the dashboard.
Two regions, one home per account, chosen when you sign up and create your first API key: EU (eu.api.complyedge.io, key prefix ce_eu_) or US (api.complyedge.io, key prefix ce_). The SDK reads the prefix and picks the host. To change the region later, use Request a region change in the dashboard; you get a new key for it. base_url, region, COMPLYEDGE_API_URL, and COMPLYEDGE_REGION only choose which host to call. They do not change the account's region.
The region is where your checks run and your audit records are stored. The prompt and the AI's answer are never stored. On a paid plan, after the phrase rules pass, the
Solo se muestra el principio; lee el resto en el repo