Pinpole MCP Server

Pinpole MCP Server

Enables AI agents to design cloud architectures, run cost/performance simulations, and draw them on a Pinpole canvas directly from Claude Code, Cursor, and OpenAI Codex.

Category
访问服务器

README

Pinpole MCP Server

Design cloud architectures, run cost/performance simulations, and draw them on your Pinpole canvas — directly from Claude Code, Cursor, and OpenAI Codex. A draw.io replacement driven by your AI agent.

Product: https://pinpole.cloud · App: https://app.pinpole.cloud


What it does

Your coding agent can now talk to Pinpole over the Model Context Protocol:

Tool What it does Auth
pinpole_build_architecture Flagship. Prompt → validated architecture → drawn on your canvas. Returns a canvas URL. Optional cost simulation. token
pinpole_create_architecture Generate a {nodes, edges} graph from a prompt (no drawing). token
pinpole_simulate_cost Run the simulation engine over a graph at a traffic level → per-node + total monthly cost, latency p50/p95/p99, throttling alerts. none
pinpole_draw_on_canvas Persist a graph to your canvas (creates project/workspace if needed). Auto-layout. token
pinpole_open_canvas Get the canvas deep link for a project/workspace. none
pinpole_list_projects / pinpole_create_project Manage projects. token
pinpole_export_terraform Generate Terraform from a graph (offline). none
pinpole_list_services List AWS service ids the canvas understands (local repo only). none

A typical flow: the agent calls pinpole_build_architecture with a description, Pinpole's AWS Well-Architected model designs it, the nodes + connections appear on your canvas, and the agent hands you a URL to open the live, editable diagram.


1. Get a token

Open Pinpole → Settings → Developer / MCP and create a personal access token (pp_live_…). Copy it — it's shown only once.

Tokens act on behalf of your account (create projects/workspaces, draw on the canvas, use AI-architect credits). Revoke any token from the same screen.

2. Configure your agent

Claude Code

claude mcp add pinpole \
  --env PINPOLE_API_TOKEN=pp_live_… \
  --env PINPOLE_BASE_URL=https://app.pinpole.cloud \
  -- npx -y @pinpole/mcp

Or commit .mcp.json to a repo (see examples/claude-code.mcp.json).

Cursor

Add to ~/.cursor/mcp.json (or .cursor/mcp.json in a project) — see examples/cursor.mcp.json:

{
  "mcpServers": {
    "pinpole": {
      "command": "npx",
      "args": ["-y", "@pinpole/mcp"],
      "env": {
        "PINPOLE_API_TOKEN": "pp_live_…",
        "PINPOLE_BASE_URL": "https://app.pinpole.cloud"
      }
    }
  }
}

OpenAI Codex

Add to ~/.codex/config.toml — see examples/codex-config.toml:

[mcp_servers.pinpole]
command = "npx"
args = ["-y", "@pinpole/mcp"]
env = { PINPOLE_API_TOKEN = "pp_live_…", PINPOLE_BASE_URL = "https://app.pinpole.cloud" }

Environment variables

Variable Default Notes
PINPOLE_API_TOKEN Personal access token (pp_live_…). Sent as Authorization: Bearer.
PINPOLE_BASE_URL https://app.pinpole.cloud Point at a local server for testing.
PINPOLE_DEV_USER_ID Local dev only. Sent as x-pinpole-dev-userid (requires the server to run with ALLOW_DEV_USER_HEADER=1). Lets you test without a token.

Local development & testing

From the Pinpole repo:

npm run mcp:build           # compile mcp/ → mcp/dist
ALLOW_DEV_USER_HEADER=1 npm run dev   # start the app (default :3031 via `npm start`, :3000 via dev)

Then point your agent at the local build with the dev header — see examples/local-dev.mcp.json. PINPOLE_DEV_USER_ID is your Firebase uid.

Smoke-test the tool list without an agent:

printf '%s\n' \
 '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2024-11-05","capabilities":{},"clientInfo":{"name":"x","version":"0"}}}' \
 '{"jsonrpc":"2.0","method":"notifications/initialized"}' \
 '{"jsonrpc":"2.0","id":2,"method":"tools/list","params":{}}' \
 | node mcp/dist/server.js

Or use the inspector: npx @modelcontextprotocol/inspector node mcp/dist/server.js.

HTTP / remote connector mode

npm run mcp:http serves a Streamable-HTTP endpoint at POST /mcp (with the minimal OAuth scaffolding Claude's custom-connector probe expects). Env: MCP_HOST, MCP_PORT (default 3333).


Links

  • Pinpole — https://pinpole.cloud
  • App — https://app.pinpole.cloud
  • Issues & source — https://github.com/codeforstartups/pinpole-mcp

MIT licensed.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选