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)
Zero-secret MCP gateway for AI agents: risk-scored, audited calls with human-in-the-loop approval.
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。
Authorization标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。
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 …”。
这个地址需要在请求的 header 中放入密钥,而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。
在终端中运行这条命令
claude mcp add --transport http gateway https://api.identark.io/v1/mcp/rpc --header 'Authorization: your-value'运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"gateway": {
"url": "https://api.identark.io/v1/mcp/rpc",
"headers": {
"Authorization": "your-value"
}
}
}
}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": {
"gateway": {
"type": "http",
"url": "https://api.identark.io/v1/mcp/rpc",
"headers": {
"Authorization": "your-value"
}
}
}
}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。
这个地址需要在请求的 header 中放入密钥,而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。
你的选择通过 Cookie 保存在这台设备上,无需账户。
Authorization 机密 必填 HTTP header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6日
注册名称已通过域名 identark.io 验证(注册中心会核实域名所有权)
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。
你需要填写:Authorization
它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。
GitHub 仓库最后更新于–,最新版本(0.1.0)于4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, Fomu 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.
Kenya government form guides: checklists, draft letters, eCitizen, Huduma, timelines. Sample data.
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。
The AgentGateway Protocol — secure, scalable AI agent execution infrastructure.
When an AI agent can execute code, call APIs, or access files, it runs in a process. That process has an environment. That environment typically contains everything that can cause serious damage: LLM API keys, database credentials, AWS tokens.
The naive solution — run your agent on the same backend as your REST API — creates two problems at once:
identark solves both.
The SDK implements the AgentGateway Protocol — a clean interface between your agent logic and the outside world. Two implementations ship out of the box:
| Gateway | When to use | Credentials | History |
|---|---|---|---|
DirectGateway | Local development, CI evals | Your API key | In-memory |
ControlPlaneGateway | Production on IdentArk | Zero — none in the agent | Control plane DB |
Your agent code is identical in both environments. The switch is two lines.
pip install identark[openai]
import asyncio
from openai import AsyncOpenAI from identark import DirectGateway, Message, Role
async def main(): gateway = DirectGateway( llm_client=AsyncOpenAI(), # Your API key — not in the agent loop model="gpt-4o", )
response = await gateway.invoke_llm( new_messages=[Message(role=Role.USER, content="Hello, IdentArk!")] )
print(response.message.content) print(f"Cost: ${response.cost_usd:.6f}")
asyncio.run(main())
Change two lines. Your agent logic is untouched.
# Before (local)
from identark import DirectGateway gateway = DirectGateway(llm_client=AsyncOpenAI(), model="gpt-4o")
from identark import ControlPlaneGateway gateway = ControlPlaneGateway() # auto-detects env vars inside a IdentArk sandbox
The agent asks the control plane to act; the provider key (Stripe, Paystack, GitHub or AWS) stays in IdentArk. Grants, budgets and human approval apply before anything executes, and a reused idempotency key never acts twice.
request = await gateway.request_capability(
"payments.payment_link.create", "paystack", {"amount_minor": 1_500_000, "currency": "NGN", "customer_email": "buyer@example.com", "reference": "order-1001"}, idempotency_key="order-1001-link", )
execution = await gateway.get_capability_execution(request["request_id"])
# Core SDK only
pip install identark
pip install identark[openai]
pip install identark[anthropic]
pip install identark[gemini]
pip install identark[mistral]
pip install identark[all]
Requirements: Python 3.10+
Using TypeScript? The parity SDK ships as the zero-runtime-dependency identark npm package, with the same AgentGateway contract and structured credential sessions.
IdentArk is designed from the ground up to work with any LLM provider, including those that keep your data inside the UK or EU. The AgentGateway Protocol decouples your agent logic from the inference provider — switching providers requires changing one line.
from openai import AsyncOpenAI
from identark import DirectGateway
gateway = DirectGateway( llm_client=AsyncOpenAI( base_url="http://localhost:11434/v1", api_key="ollama", ), model="llama3.2", provider="local", # forces $0 cost tracking; inference stays on your machine )
Install Ollama: brew install ollama && ollama pull llama3.2 && ollama serve
from openai import AsyncOpenAI
from identark import DirectGateway
gateway = DirectGateway( llm_client=AsyncOpenAI( base_url="https://api.mistral.ai/v1", api_key="your-mistral-api-key", ), model="mistral-small-latest", # auto-detected as "mistral" provider )
Mistral AI is a French company. All inference runs in EU data centres, subject to EU data protection law (GDPR). Use this when UK/EU data governance requirements prohibit sending inference traffic to US-based cloud providers.
See examples/ for complete runnable scripts.
Any class implementing these four async methods is a valid gateway:
class AgentGateway(Protocol):
async def invoke_llm(self, new_messages, tools=None, tool_choice="auto") -> LLMResponse: ... async def persist_messages(self, messages) -> None: ... async def request_file_url(self, file_path, method="PUT") -> PresignedURL: ... async def get_session_cost(self) -> float: ...
Write your agent against the protocol. The implementation — local or production — is a runtime detail.
ControlPlaneGateway holds no API keys, database credentials, or cloud tokensinvoke_llm call returns cost_usd; get_session_cost() returns the running totalDirectGateway out of the boxpy.typed marker; works with mypy strict modefrom identark.testing import MockGateway
from identark.models import LLMResponse, Message, Role
async def test_my_agent(): mock = MockGateway() mock.queue_response(LLMResponse( message=Message(role=Role.ASSISTANT, content="The answer is 42."), cost_usd=0.001, model="mock", finish_reason="stop", ))
result = await my_agent(gateway=mock)
assert mock.invoke_llm_call_count == 1 assert mock.total_messages_sent == 1
| Provider | Data residency | DirectGateway | GeminiGateway | ControlPlaneGateway |
|---|---|---|---|---|
| OpenAI (gpt-4o, gpt-4o-mini, …) | US | ✓ | — | ✓ |
| Anthropic (Claude models) | US | ✓ | — | ✓ |
| Google Gemini | Varies | ✓* | ✓ | Roadmap |
| Mistral AI | Varies | ✓ | — | ✓ |
| Kimi / Moonshot | Varies | ✓* | — | ✓ |
| Azure OpenAI | Configured Azure region | ✓* | — | ✓ |
| AWS Bedrock | Configured AWS region | — | — | ✓ |
| OpenRouter | Provider-dependent | ✓* | — | ✓ |
| Ollama | Local 🏠 | ✓ | — | Not a hosted route |
| Any OpenAI-compatible endpoint | Varies | ✓ | — | ✓ (custom endpoint) |
*Via an OpenAI-compatible client/base URL. Use GeminiGateway for native Gemini SDK features.
from identark.exceptions import CostCapExceededError, RateLimitError, IdentArkError
try: response = await gateway.invoke_llm(new_messages=[...]) except CostCapExceededError as e: print(f"Cost cap of ${e.cap_usd} reached. Spent: ${e.consumed_usd}") except RateLimitError as e: await asyncio.sleep(e.retry_after_seconds) except IdentArkError as e:
raise
Full exception hierarchy: IdentArkError > GatewayError > ControlPlaneError > AuthenticationError | CostCapExceededError | SessionNotFoundError
┌─────────────────────────────────────┐
│ Your Agent Code │ │ (depends only on AgentGateway) │ └──────────────┬──────────────────────┘ │ ┌──────────▼──────────┐ │ AgentGateway │ ← Protocol (interface) │ Protocol │ └──────┬────────┬──────┘ │ │ ┌────────▼─┐ ┌───▼──────────────┐ │ Direct │ │ ControlPlane │ │ Gateway │ │ Gateway │ │ │ │ │ │ Local / │ │ Production │ │ Evals │ │ (zero secrets) │ └──────────┘ └────────┬─────────┘ │ HTTP ┌────────▼─────────┐ │ IdentArk │ │ Control Plane │ │ (holds creds) │ └──────────────────┘
Contributions are welcome. Please open an issue before submitting significant changes.
git clone https://github.com/identark/identark.git
cd identark pip install -e ".[dev]" pre-commit install pytest tests/unit/
See CONTRIBUTING.md for full guidelines.
IdentArkChatModel)IdentArkLLM)invoke_llm_stream)IdentArkNode, IdentArkStreamNode)identark-cli for one-command control plane deploymentThe IdentArk SDK is licensed under the MIT License — free for any use, including commercial and closed-source projects. See LICENSE.
The IdentArk control plane (hosted service) is proprietary. The SDK works with any AgentGateway backend, including fully self-hosted ones.
*Built on the control plane pattern described in How We Built Secure, Scalable Agent Sandbox Infrastructure.*