原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Agentstack MCP

作者:inity13版本 1.0.1i★ –i电脑或云端
注册名称io.github.inity13/agentstack-mcp

安装

概览

作者提供的说明(英文原文)

Deterministic reasoning stack for AI agents: simulate, decide & compute, plus cross-domain tools.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

你需要

  • 在云端运行无需安装任何东西,通过互联网连接
  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

适用于网页版、桌面版和手机版 Claude:

  1. 打开 Settings → Connectors
  2. 点击 Add custom connector
  3. 粘贴下面的地址,然后点击 Add
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Add2https://…3
https://agentstack-mcp.pages.dev/mcp

或者在你的电脑上运行

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "agentstack": {
      "command": "npx",
      "args": [
        "-y",
        "agentstack-mcp"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add --transport http agentstack https://agentstack-mcp.pages.dev/mcp

或者在你的电脑上运行

claude mcp add agentstack -- npx -y agentstack-mcp

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "agentstack": {
      "url": "https://agentstack-mcp.pages.dev/mcp"
    }
  }
}

或者在你的电脑上运行

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "agentstack": {
      "command": "npx",
      "args": [
        "-y",
        "agentstack-mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "agentstack": {
      "type": "http",
      "url": "https://agentstack-mcp.pages.dev/mcp"
    }
  }
}

或者在你的电脑上运行

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "agentstack": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "agentstack-mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

ChatGPT 只能连接互联网上的服务器:

  1. 打开网页版 ChatGPT → Settings → Connectors (Apps)
  2. 点击 Create 或 Add(部分套餐需要先在 Advanced 中开启 Developer mode)
  3. 粘贴下面的地址,起个名字,然后保存
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Create2https://…3
https://agentstack-mcp.pages.dev/mcp

菜单名称可能因套餐和版本不同而略有差异。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 inity13 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    端点有响应

    尚未检查;我们会轮流检查各个端点

  • … 尚未检查

    使用 OAuth 登录

    尚未检查;我们会轮流检查各个端点

  • … 尚未检查

    工具描述中没有隐藏指令

    尚未检查;我们会在检查端点时读取工具列表

与“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32606 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32606 个服务器的 23% 更新
  • 基础检查结果等于或优于此分类中其他 32606 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Agentstack MCP 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

两种方式都可以:安装在你的电脑上,或者连接云端版本。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(1.0.1)于3个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, Georgia MCP

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211前天更新
安装

Georgia MCP

作者:abgeo

An MCP server for Georgian public data, read from the organizations that publish it.

电脑或云端今天更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

AgentStack MCP

One deterministic reasoning stack for AI agents — behind a single Model Context Protocol (MCP) endpoint and one API key:

simulate (ScenarioSim) → decide (DecisionMatrix) → compute (PrecisionCalc)

plus cross-domain composite tools that chain the three. Every number runs through decimal.js at 40-digit precision (never floats), so identical inputs always produce byte-identical output. The server is stateless — no database, no sessions.

AgentStack bundles three standalone MCP servers so an agent installs one server, uses one key, and can run reasoning that spans all three domains. It imports the same engines directly (no HTTP proxying) — zero added latency, no cascading failure.

🌐 Live hosted server (free, no install)

https://agentstack-mcp.pages.dev/mcp
{ "mcpServers": { "agentstack": {

"type": "http", "url": "https://agentstack-mcp.pages.dev/mcp" } } }

Free tier: no key, 20 calls/day per IP. Paid plans (Starter $19/mo · 8,000/day, Pro $59/mo · 80,000/day) return an API key sent as X-API-Key. One key covers all three products and the composites — about half the cost of subscribing to them separately. Landing page: https://agentstack-mcp.pages.dev.


The three namespaces (24 tools)

namespaceenginetools
sim_*ScenarioSim — what-if / scenario simulationsim_run, sim_sensitivity, sim_break_even, sim_compare, sim_list_templates
decide_*DecisionMatrix — multi-criteria decision analysisdecide, decide_score, decide_sensitivity, decide_compare_two, decide_list_methods
calc_*PrecisionCalc — exact finance/business mathcalc_metric, calc_list_metrics, calc_currency_convert, calc_business_days, calc_compound_growth, calc_npv, calc_irr, calc_loan_amortization, calc_depreciation
meta—list_capabilities, health_check

Note on two deliberately-namespaced collisions: sim_sensitivity varies

*scenario inputs*; decide_sensitivity varies *criteria weights*. They are

different operations — the prefix disambiguates them for the agent.

Composite tools — the reason to use the stack

Deterministic end-to-end; each chains engines that no single server bundles:

ToolPipelineWhat it does
plan_to_valuationsimulate → computeProject a scenario, take a per-period cash-flow line (cashflow_metric), and value it: NPV at a discount rate, IRR, undiscounted total. initial_investment becomes the period-0 outflow (needed for IRR).
evaluate_options_with_scenariossimulate → decideProject each option as its own scenario, then rank the options against weighted criteria drawn from the scenario outcomes (key_results).
stress_test_decisionsimulate × decideStress one scenario assumption across every option and report how often the baseline winner survives (robustness) and where it flips.

Composite responses report the pipeline they ran and carry each stage's structured output, so an agent can drill into any step.

Profiles — fight tool-selection noise

Append ?profile= to the endpoint to load only a subset:

profiletools
all *(default)*every tool (24)
financecalc_* + plan_to_valuation + meta
decisiondecide_* + evaluate_options_with_scenarios + stress_test_decision + meta
simulationsim_* + all composites + meta
{ "mcpServers": { "agentstack": {

"url": "https://agentstack-mcp.pages.dev/mcp?profile=finance" } } }


Response envelope

Namespaced tools return the exact envelope of their underlying product. Composite tools add composite, pipeline, per-stage blocks, methodology, notes, and a plain-language explanation. Errors are always structured data:

{ "status": "error", "error": { "type": "unknown_metric", "message": "...", "hint": "..." } }

Example — plan_to_valuation (trimmed):

{

"status": "success", "composite": "plan_to_valuation", "pipeline": ["scenariosim.run_scenario", "precisioncalc.net_present_value", "precisioncalc.internal_rate_of_return"], "scenario": { "template": "saas_growth", "horizon": 12, "key_results": { "ending_mrr": 26982.1 } }, "cashflow_metric": "mrr", "cashflows": [-150000, 14040, 15600, "..."], "valuation": { "discount_rate": 0.01, "npv": 11157.386023, "irr": 0.02504, "value_creating": true }, "explanation": "Projecting 'saas_growth' over 12 month(s) and valuing the 'mrr' stream at 1%/period gives an NPV of ..." }


Project structure

agentstack-mcp/

├── worker-src/ │ ├── index.mjs # Cloudflare Pages Function: MCP transport, namespacing, profiles, billing │ ├── composites.mjs # the 3 cross-domain tools (simulate -> decide -> compute) │ ├── billing.mjs # Stripe + KV: one key / one quota for the whole stack │ └── engines/ # vendored, unmodified product engines (100% deterministic) │ ├── scenariosim.mjs │ ├── decisionmatrix.mjs │ └── precisioncalc.mjs ├── server.mjs # local stdio MCP server (same engines + composites; AGENTSTACK_PROFILE env) ├── site/ # landing page + mcp.json + llms.txt + _worker.js (built) ├── tests/composites.test.mjs ├── examples/agent_example.mjs ├── scripts/sync-engines.sh # re-vendor engines from the sibling repos ├── package.json · wrangler.toml · server.json · smithery.yaml · Dockerfile · LICENSE └── README.md

Why vendor the engines? So this repo is self-contained and reproducible. The engines are the *same* deterministic modules that power the three standalone servers; npm run sync-engines re-copies them from the sibling repos when an upstream change lands.


Run it locally

git clone <your-fork> agentstack-mcp && cd agentstack-mcp

npm install npm test # composite-logic tests (no network) npm run dev # -> http://127.0.0.1:8788/mcp node examples/agent_example.mjs # hosted demo node examples/agent_example.mjs http://127.0.0.1:8788 node server.mjs # dependency-light stdio server (AGENTSTACK_PROFILE=finance to subset)

Quick manual call:

curl -s http://127.0.0.1:8788/mcp \

-H 'content-type: application/json' -H 'accept: application/json, text/event-stream' \ -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"list_capabilities","arguments":{}}}'


Install via npm (stdio, no hosting)

Run the server locally over stdio with a single command — nothing to deploy:

npx -y agentstack-mcp

Claude Desktop / any stdio MCP client (claude_desktop_config.json):

{ "mcpServers": { "agentstack": { "command": "npx", "args": ["-y", "agentstack-mcp"] } } }

This is the same deterministic engine as the hosted server, running on your machine.

Client configuration

Cursor — ~/.cursor/mcp.json
{ "mcpServers": { "agentstack": { "url": "https://agentstack-mcp.pages.dev/mcp" } } }
Claude Desktop — claude_desktop_config.json (via mcp-remote)
{ "mcpServers": { "agentstack": { "command": "npx", "args": ["-y", "mcp-remote", "https://agentstack-mcp.pages.dev/mcp"] } } }
VS Code — .vscode/mcp.json
{ "servers": { "agentstack": { "type": "http", "url": "https://agentstack-mcp.pages.dev/mcp" } } }
Windsurf — ~/.codeium/windsurf/mcp_config.json
{ "mcpServers": { "agentstack": { "serverUrl": "https://agentstack-mcp.pages.dev/mcp" } } }

Add "headers": { "X-API-Key": "ssak_live_..." } once you have a key.


Example composite payloads

Rank growth strategies on their projected outcomes:

{ "name": "evaluate_options_with_scenarios", "arguments": {

"template": "saas_growth", "horizon": 12, "options": [ { "name": "Aggressive", "inputs": { "new_customers_per_period": 60, "churn_rate": 0.05 } }, { "name": "Lean", "inputs": { "new_customers_per_period": 20, "churn_rate": 0.02 } } ], "criteria": [ { "metric": "ending_mrr", "weight": 3, "direction": "benefit" }, { "metric": "total_churned_customers", "weight": 1, "direction": "cost" } ] } }

Value a plan's MRR stream:

{ "name": "plan_to_valuation", "arguments": {

"template": "saas_growth", "horizon": 12, "inputs": { "new_customers_per_period": 60, "churn_rate": 0.05, "arpu": 60 }, "cashflow_metric": "mrr", "rate": 0.01, "initial_investment": 150000 } }

Stress-test the decision:

{ "name": "stress_test_decision", "arguments": {

"template": "saas_growth", "horizon": 12, "options": [ { "name": "Aggressive", "inputs": { "churn_rate": 0.05 } }, { "name": "Lean", "inputs": { "churn_rate": 0.02 } } ], "criteria": [ { "metric": "ending_mrr", "weight": 3 } ], "stress": { "variable": "churn_rate", "variation": 0.5, "steps": 5 } } }


Deploy on Cloudflare Pages

npm install

npx wrangler login npm run deploy # esbuild -> site/_worker.js, then wrangler pages deploy

Runs fully free / private with no bindings or secrets (fails open on the free tier). For billing: bind a KV namespace AGENTSTACK_KV, set PRICE_STARTER / PRICE_PRO in [vars], and add Stripe secrets:

wrangler pages secret put STRIPE_SECRET_KEY    --project-name agentstack-mcp

wrangler pages secret put STRIPE_WEBHOOK_SECRET --project-name agentstack-mcp

Routes: /mcp (Streamable HTTP), /checkout, /success, /portal, /webhook, /metrics.

Auth & rate limiting

Enforced in worker-src/billing.mjs: identify() reads X-API-Key / Authorization: Bearer and falls back to per-IP free tier; consumeQuota() is a KV daily counter (the single gating point). One key / one quota spans the whole stack. Marked NOTE (auth) / NOTE (rate limiting) seams show where to swap in JWT/mTLS or a token-bucket. None of it touches the deterministic math.

Relationship to the standalone servers

AgentStack is additive, not a replacement. The three products keep running on their own for single-domain use:

License

MIT — see LICENSE.

问 PopNx