Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者提供的说明(英文原文)
Deterministic reasoning stack for AI agents: simulate, decide & compute, plus cross-domain tools.
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。
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。
选择你使用的 AI 应用,然后复制设置。
你需要
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:
https://agentstack-mcp.pages.dev/mcp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/mcpclaude mcp add agentstack -- npx -y agentstack-mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"agentstack": {
"url": "https://agentstack-mcp.pages.dev/mcp"
}
}
}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。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"agentstack": {
"type": "http",
"url": "https://agentstack-mcp.pages.dev/mcp"
}
}
}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:
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。
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。
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
注册名称已通过 GitHub 账户 inity13 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
尚未检查;我们会轮流检查各个端点
尚未检查;我们会轮流检查各个端点
尚未检查;我们会在检查端点时读取工具列表
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。
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。
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。
两种方式都可以:安装在你的电脑上,或者连接云端版本。
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。
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。
同一分类中有:Spec Driven Development, Remote Desktop Commander, Georgia MCP
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
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.
An MCP server for Georgian public data, read from the organizations that publish it.
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。
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.
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.
| namespace | engine | tools |
|---|---|---|
sim_* | ScenarioSim — what-if / scenario simulation | sim_run, sim_sensitivity, sim_break_even, sim_compare, sim_list_templates |
decide_* | DecisionMatrix — multi-criteria decision analysis | decide, decide_score, decide_sensitivity, decide_compare_two, decide_list_methods |
calc_* | PrecisionCalc — exact finance/business math | calc_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_sensitivityvaries
*scenario inputs*;
decide_sensitivityvaries *criteria weights*. They are
different operations — the prefix disambiguates them for the agent.
Deterministic end-to-end; each chains engines that no single server bundles:
| Tool | Pipeline | What it does |
|---|---|---|
plan_to_valuation | simulate → compute | Project 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_scenarios | simulate → decide | Project each option as its own scenario, then rank the options against weighted criteria drawn from the scenario outcomes (key_results). |
stress_test_decision | simulate × decide | Stress 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.
Append ?profile= to the endpoint to load only a subset:
| profile | tools |
|---|---|
all *(default)* | every tool (24) |
finance | calc_* + plan_to_valuation + meta |
decision | decide_* + evaluate_options_with_scenarios + stress_test_decision + meta |
simulation | sim_* + all composites + meta |
{ "mcpServers": { "agentstack": {
"url": "https://agentstack-mcp.pages.dev/mcp?profile=finance" } } }
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 ..." }
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.
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":{}}}'
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.
~/.cursor/mcp.json{ "mcpServers": { "agentstack": { "url": "https://agentstack-mcp.pages.dev/mcp" } } }
claude_desktop_config.json (via mcp-remote){ "mcpServers": { "agentstack": { "command": "npx", "args": ["-y", "mcp-remote", "https://agentstack-mcp.pages.dev/mcp"] } } }
.vscode/mcp.json{ "servers": { "agentstack": { "type": "http", "url": "https://agentstack-mcp.pages.dev/mcp" } } }
~/.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.
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 } } }
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.
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.
AgentStack is additive, not a replacement. The three products keep running on their own for single-domain use:
MIT — see LICENSE.