final-approval
Servidor MCP FinalApproval
Servidor Model Context Protocol independiente para FinalApproval — protege las acciones de los agentes de IA mediante aprobación humana.
Tu agente llama a submit_approval; un humano revisa en una página personalizada en tu panel de FinalApproval; el webhook configurado del canal se activa cuando el humano toma una decisión.
Esta es la variante stdio destinada a uso local / headless / CI / indexado por directorios (Glama). Si prefieres el servidor Streamable-HTTP alojado con OAuth, apunta los clientes MCP a https://www.finalapproval.ai/mcp.
Alcance
v0.1 expone una herramienta:
Herramienta | Estado | Notas |
| ✅ enviado | Crea una aprobación pendiente. El webhook se activa al resolverse. |
| planeado | Bloqueado en |
| planeado | Bloqueado en |
| planeado | Bloqueado en |
Para obtener la superficie completa de herramientas hoy, utiliza el endpoint alojado en https://www.finalapproval.ai/mcp (OAuth 2.1, ámbito approvals:write).
Related MCP server: Approval Gate
Configuración
Inicia sesión en finalapproval.ai y crea un canal. Copia su clave API (comienza con
fa_) y configura una URL de webhook.Ejecuta el servidor MCP con la clave API en
FINALAPPROVAL_API_KEY.
Claude Code / Cursor (Node)
npx -y @finalapproval/mcp-serverFragmento de configuración (Claude Code ~/.claude.json):
{
"mcpServers": {
"finalapproval": {
"command": "npx",
"args": ["-y", "@finalapproval/mcp-server"],
"env": {
"FINALAPPROVAL_API_KEY": "fa_..."
}
}
}
}Docker
docker run --rm -i \
-e FINALAPPROVAL_API_KEY=fa_xxx \
ghcr.io/finalapproval/final-approval-mcp:latest(Próximamente imagen publicada; también puedes compilar localmente: docker build -t finalapproval-mcp ..)
Variables de entorno
Variable | Requerido | Predeterminado | Propósito |
| sí | — | Clave API del canal (comienza con |
| no |
| Sustitución para autoalojado / dev |
Cerrando el ciclo
submit_approval devuelve inmediatamente un ID de aprobación pendiente. La decisión real llega a través del webhook del canal, no de vuelta a través de MCP. Tu aplicación host (el servidor del agente) debe implementar un receptor de webhook que verifique la firma HMAC y ejecute la acción protegida si es approved o registre si es denied. Consulta la documentación de FinalApproval para ver el esquema de carga útil del webhook.
Desarrollo
npm install
npm run build
FINALAPPROVAL_API_KEY=fa_... npm startLicencia
MIT
Available Tools
1 toolsubmit_approvalSubmit an approval requestA
Create a pending approval in the FinalApproval channel whose API key is configured in this MCP server. The channel's webhook fires when the human approves or denies. Use this before any irreversible agent action (sending email, merging a PR, publishing a post, running a migration, etc).
| Name | Required | Description | Default |
|---|---|---|---|
| title | Yes | Short headline shown in the approval list. | |
| body | Yes | HTML body shown to the human reviewer. Tailwind utility classes are supported. Include the actual content being gated (diff, PR body, email text) — the reviewer decides from this card alone. | |
| data | No | Machine-readable payload attached to the approval. Echoed back to the channel's webhook on resolution — put the structured args your callback will need to execute the gated action. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: the approval is pending until human action, webhook firing on resolution, and the irreversible nature of gated actions. However, it lacks details on error handling, rate limits, or authentication requirements beyond the API key mention.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured in two sentences: the first defines the tool's purpose, and the second provides critical usage guidelines. Every phrase adds value, with no redundant or unnecessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description provides strong contextual completeness by explaining the approval workflow, webhook behavior, and use-case guidance. It adequately compensates for the lack of structured fields, though it could benefit from mentioning response format or error cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, providing full parameter documentation. The description adds minimal parameter semantics beyond the schema—it mentions the channel's API key context but doesn't elaborate on parameter usage or constraints. Baseline 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create a pending approval') and the target resource ('in the FinalApproval channel'), with specific context about the channel's API key configuration. It distinguishes this as a submission tool for approval requests, which is unambiguous even without sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool ('before any irreversible agent action') and lists concrete examples of such actions (sending email, merging a PR, etc.). This gives clear context for application without needing sibling tool comparisons.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
v0.1.0- First observed
submit_approval
TDQS
Scored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool has a clear and distinct purpose for submitting approvals.
The tool name 'submit_approval' follows a clear verb_noun pattern. Since there is only one tool, consistency is inherently perfect with no deviations or mixed conventions.
A single tool is too few for most practical server purposes, as it severely limits functionality and scope. While it might serve a narrow use case, it feels thin and incomplete for typical agent workflows.
The server's domain appears to be approval workflows, but with only a submit tool, there are significant gaps. Missing operations likely include checking approval status, listing pending approvals, or handling approvals programmatically, which could cause agent failures.
Maintenance
Related MCP Connectors
Give any AI agent a way to ask a person — for approval, a decision, an answer or a review.
Supervised API-write gateway for AI agents with policy, human approval and execution receipts.
Human approvals, notifications, inbound webhooks, wake-ups for headless agents. Free trial: /try
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- AlicenseNot gradedqualityDmaintenanceProvides a human approval gate for AI agents, enabling interactive inline cards for approving, editing, or rejecting actions before they are executed.MIT
- AlicenseNot gradedqualityCmaintenancePauses AI agent execution and routes approval requests to humans via Slack or email, with cryptographically signed proof of the human's decision.23 npmMIT
- AlicenseNot gradedqualityDmaintenanceEnables AI agents to request human approvals with customizable forms, webhooks, and team features.34 npmMIT