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IdentArk Gateway

作者:identArk版本 0.1.0i★ –i在云端运行
注册名称io.identark/gateway

安装

概览

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.

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。

  • 连接方式: 在云端运行
  • 传输方式: Streamable HTTP
  • 分类: 其他
  • 你需要填写:Authorization

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

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。

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": {
    "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。

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": {
    "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。

需要你填写的值

  • Authorization 机密 必填 HTTP header
    Bearer

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6日

  • ✓ 通过

    作者与仓库一致

    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)

  • … 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 32509 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32509 个服务器的 18% 更新
  • 基础检查结果等于或优于此分类中其他 32509 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

IdentArk Gateway 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?

你需要填写:Authorization

它在我的电脑上运行还是在云端?

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。

它还在维护吗?

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。

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, Fomu 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昨天更新
安装

Fomu MCP

作者:gabrielmahia

Kenya government form guides: checklists, draft letters, eCitizen, Huduma, timelines. Sample data.

在你的电脑上运行今天更新
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。

identark

The AgentGateway Protocol — secure, scalable AI agent execution infrastructure.


The problem

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:

  1. Security: The agent can access every secret on the machine.
  2. Reliability: A memory-hungry agent degrades your API. Redeploying your API kills all running agents.

identark solves both.


How it works

The SDK implements the AgentGateway Protocol — a clean interface between your agent logic and the outside world. Two implementations ship out of the box:

GatewayWhen to useCredentialsHistory
DirectGatewayLocal development, CI evalsYour API keyIn-memory
ControlPlaneGatewayProduction on IdentArkZero — none in the agentControl plane DB

Your agent code is identical in both environments. The switch is two lines.


Quick start

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())

Moving to production

Change two lines. Your agent logic is untouched.

# Before (local)

from identark import DirectGateway gateway = DirectGateway(llm_client=AsyncOpenAI(), model="gpt-4o")

After (production — agent holds zero secrets)

from identark import ControlPlaneGateway gateway = ControlPlaneGateway() # auto-detects env vars inside a IdentArk sandbox

Governed actions (payments, payment links, refunds)

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", )

"succeeded" returns the checkout link; "pending_approval" waits for a person.

execution = await gateway.get_capability_execution(request["request_id"])


Installation

# Core SDK only

pip install identark

With OpenAI support

pip install identark[openai]

With Anthropic support

pip install identark[anthropic]

With Google Gemini support

pip install identark[gemini]

With Mistral AI support (EU provider)

pip install identark[mistral]

All cloud providers

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.


Data Sovereignty

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.

Run fully local with Ollama (zero data egress)
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

Use Mistral AI (EU data residency)
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.


The AgentGateway Protocol

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.


Features

  • Zero-secret agents — ControlPlaneGateway holds no API keys, database credentials, or cloud tokens
  • Stateless by design — conversation history owned by the gateway, not the agent; kill and restart without data loss
  • Framework-agnostic — works with LangChain, LlamaIndex, raw API calls, or any custom agent framework
  • Built-in cost tracking — every invoke_llm call returns cost_usd; get_session_cost() returns the running total
  • OpenAI + Anthropic — both providers supported in DirectGateway out of the box
  • MockGateway for testing — no LLM calls in your test suite; full call recording for assertions
  • Full type annotations — py.typed marker; works with mypy strict mode

Testing your agents

from 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


Supported providers

ProviderData residencyDirectGatewayGeminiGatewayControlPlaneGateway
OpenAI (gpt-4o, gpt-4o-mini, …)US✓—✓
Anthropic (Claude models)US✓—✓
Google GeminiVaries✓*✓Roadmap
Mistral AIVaries✓—✓
Kimi / MoonshotVaries✓*—✓
Azure OpenAIConfigured Azure region✓*—✓
AWS BedrockConfigured AWS region——✓
OpenRouterProvider-dependent✓*—✓
OllamaLocal 🏠✓—Not a hosted route
Any OpenAI-compatible endpointVaries✓—✓ (custom endpoint)

*Via an OpenAI-compatible client/base URL. Use GeminiGateway for native Gemini SDK features.


Error handling

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:

Catch-all for any SDK error

raise

Full exception hierarchy: IdentArkError > GatewayError > ControlPlaneError > AuthenticationError | CostCapExceededError | SessionNotFoundError


Architecture

┌─────────────────────────────────────┐

│ 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) │ └──────────────────┘


Community


Contributing

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.


Roadmap

  • LangChain adapter (IdentArkChatModel)
  • LlamaIndex adapter (IdentArkLLM)
  • Streaming support (invoke_llm_stream)
  • CrewAI integration
  • LangGraph integration (IdentArkNode, IdentArkStreamNode)
  • Pluggable inference backends (distributed compute)
  • identark-cli for one-command control plane deployment

License

The 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.*

问 PopNx