FinalApproval을 위한 독립형 Model Context Protocol 서버 — AI 에이전트의 작업을 인간의 승인 뒤에 배치합니다.
에이전트가 submit_approval을 호출하면, 사람이 FinalApproval 대시보드의 브랜드 페이지에서 검토하며, 사람이 결정을 내리면 채널에 구성된 웹훅이 다시 실행됩니다.
이것은 로컬 / 헤드리스 / CI / 디렉토리 인덱스(Glama)용으로 의도된 stdio 변형입니다. 호스팅된 OAuth 게이트 Streamable-HTTP 서버를 원하시면 MCP 클라이언트를 https://www.finalapproval.ai/mcp로 지정하십시오.
v0.1은 하나의 도구를 제공합니다:
도구 | 상태 | 참고 |
| ✅ 출시 | 보류 중인 승인을 생성합니다. 해결 시 웹훅이 실행됩니다. |
| 계획 중 | 공개 |
| 계획 중 | 공개 |
| 계획 중 | 공개 |
현재 전체 도구 기능을 사용하려면 https://www.finalapproval.ai/mcp (OAuth 2.1, 범위 approvals:write)의 호스팅된 엔드포인트를 사용하십시오.
Related MCP server: Approval Gate
finalapproval.ai에 로그인하여 채널을 만듭니다. API 키(fa_로 시작)를 복사하고 웹훅 URL을 구성합니다.
FINALAPPROVAL_API_KEY에 API 키를 설정하여 MCP 서버를 실행합니다.
npx -y @finalapproval/mcp-server구성 스니펫 (Claude Code ~/.claude.json):
{
"mcpServers": {
"finalapproval": {
"command": "npx",
"args": ["-y", "@finalapproval/mcp-server"],
"env": {
"FINALAPPROVAL_API_KEY": "fa_..."
}
}
}
}docker run --rm -i \
-e FINALAPPROVAL_API_KEY=fa_xxx \
ghcr.io/finalapproval/final-approval-mcp:latest(게시된 이미지가 곧 제공될 예정입니다. 로컬에서 빌드할 수도 있습니다: docker build -t finalapproval-mcp .)
변수 | 필수 | 기본값 | 목적 |
| 예 | — | 채널 API 키 ( |
| 아니오 |
| 자체 호스팅 / 개발용 재정의 |
submit_approval은 보류 중인 승인 ID와 함께 즉시 반환됩니다. 실제 결정은 MCP를 통하지 않고 채널의 웹훅을 통해 도착합니다. 호스트 애플리케이션(에이전트의 서버)은 HMAC 서명을 확인하고 approved 시 게이트된 작업을 실행하거나 denied 시 기록하는 웹훅 수신기를 구현해야 합니다. 웹훅 페이로드 스키마는 FinalApproval 문서를 참조하십시오.
npm install
npm run build
FINALAPPROVAL_API_KEY=fa_... npm startMIT
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. |
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.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v0.1.0submit_approvalScored 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.
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