Gluo
Free agent tools, no sign-in: browser flows, test inboxes, web extract, site and security scans.
作者提供的说明(英文原文)
Secure MCP server framework with 23 security layers and ML threat detection. Zero deps.
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 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"aegisgate": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/aegisgatesecurity/aegisgate-mcp:1.5.1"
]
}
}
}在终端中运行这条命令
claude mcp add aegisgate -- docker run -i --rm ghcr.io/aegisgatesecurity/aegisgate-mcp:1.5.1粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"aegisgate": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/aegisgatesecurity/aegisgate-mcp:1.5.1"
]
}
}
}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": {
"aegisgate": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/aegisgatesecurity/aegisgate-mcp:1.5.1"
]
}
}
}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。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
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。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
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8日
注册名称已通过 GitHub 账户 aegisgatesecurity 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
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
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。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(1.5.1)于28天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Docker。
同一分类中有:Gluo, Seal Security, Zeqqat
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:↓ 每周下载量i★ 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
Free agent tools, no sign-in: browser flows, test inboxes, web extract, site and security scans.
Vulnerability management: scan projects, search sealed packages, manage sealing rules and reports.
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。
Secure MCP server framework — 23 layers of defense, zero dependencies.
*A hardened, zero-dependency MCP server written in pure Go. Build your MCP server on a foundation that has security built in from line one — not bolted on after a breach.*
Apache 2.0 · 23 security layers · 79 regex patterns + CharCNN-BiLSTM (v15) ML detection · Zero CVEs · Zero external module dependencies
Found AegisGate MCP useful? [Star the repo](https://github.com/aegisgatesecurity/aegisgate-mcp) ⭐ and [tell a colleague](https://x.com/intent/tweet?text=Securing%20my%20MCP%20servers%20with%20AegisGate%20%E2%80%94%2023%20security%20layers%2C%20zero%20dependencies%2C%20ML%20threat%20detection%3A%20https%3A%2F%2Fgithub.com%2Faegisgatesecurity%2Faegisgate-mcp) — it helps other devs discover secure MCP tooling.
Quick Start · Security Layers · RBAC · Architecture · Protocol · Docs · Releases
AegisGate Security™ is a trademark of AegisGate Security, LLC, filed with the USPTO.
"AegisGate MCP" is an unregistered product name. See Trademark below.
38% of MCP servers have no authentication. 590+ security advisories. 3 critical CVEs in the official MCP SDKs in 6 months — including CVSS 9.8 remote code execution and the "Mother of All AI Supply Chains" flaw affecting 150M+ downloads.
The official MCP SDKs give you the protocol. They don't give you security. No authentication. No audit logging. No threat detection. No rate limiting. No RBAC. Every server built on a bare SDK starts with a blank security posture and it's on you to build it — or skip it, as 38% of servers do.
AegisGate MCP is the secure alternative. Build your MCP server on a foundation that has security built in from line one — not bolted on after a breach.
| Official MCP SDKs | AegisGate MCP | |
|---|---|---|
| Authentication | ❌ Bring your own | ✅ Bearer tokens + API keys + lockout |
| Authorization | ❌ Nothing | ✅ 4-tier RBAC with per-tool permissions |
| Audit logging | ❌ Nothing | ✅ Tamper-evident SHA-256 hash chain |
| Threat detection | ❌ Nothing | ✅ 79 regex patterns + neural ML (<1ms) |
| Supply chain risk | ❌ npm/PyPI deps | ✅ Zero dependencies (Go stdlib only) |
| CVEs | 3 critical in 6 months | Zero. Ever. |
| License | MIT | Apache 2.0 |
23 security layers. 79 regex patterns. Zero dependencies. Zero CVEs. Apache 2.0.
Need proxy mode, OAuth, SIEM, or compliance frameworks? See
When to Upgrade to AegisGate Platform
below — or explore [AegisGate Rampart](https://github.com/aegisgatesecurity/aegisgate-rampart)
for local AI API proxy protection.
AegisGate MCP is a hardened, zero-dependency MCP server written in pure Go. It sits between AI agents and the tools they call, applying 23 layers of defense to every request — from authentication and RBAC to neural threat detection and chain analysis.
Standard MCP servers assume a trusted local environment. In production — whether that's a cloud SaaS platform, an enterprise data pipeline, or an air-gapped plant network — agents may execute commands, query databases, or interact with critical systems. A single unauthorized or malicious tool call can cause data exfiltration, process disruption, or worse. AegisGate MCP wraps every tool call in defense-in-depth, all with zero external module dependencies so it can run air-gapped.
| Version | 1.6.1 |
| License | Apache-2.0 |
| Go version | 1.27+ |
| Module deps | Zero (no require directives — all third-party code vendored) |
| Docker image | ML: debian:bookworm-slim (gnutls purged), ~127 MB, 0 CVEs · Lite: distroless/static-debian12, ~10 MB, 0 CVEs |
| Architectures | amd64, arm64 |
| ML model | CharCNN-BiLSTM v15, 1.6M params, <1ms CPU inference |
| Tests | 611 unit/integration + 32 load/stress = 643 total, 14 benchmarks, 3 fuzz targets, 92.0% coverage (non-CGO) / 91.9% (CGO) |
go build -o mcp-server ./cmd/mcp-server
# Basic TCP server on :8081
./mcp-server
./mcp-server --token my-secret --audit /var/log/mcp-audit.json
./mcp-server --demo
./mcp-server --transport stdio --demo
./mcp-server --transport http --addr :8081 --demo
./mcp-server --tls --tls-cert server.pem --tls-key server.key --tls-client-ca ca.pem
./mcp-server --config /etc/mcp/config.json --health-addr :8082
# Build and run (ML-enabled, ~127 MB, 0 CVEs)
docker build --target ml -t aegisgate-mcp . docker run -p 8081:8081 aegisgate-mcp --demo
docker run -p 8081:8081 \ -e MCP_AUTH_TOKEN=your-secret-token \ -e MCP_DEMO_TOOLS=true \ aegisgate-mcp
docker build --build-arg CGO_ENABLED=0 --target lite -t aegisgate-mcp:lite . docker run -p 8081:8081 aegisgate-mcp:lite --demo
The ML image uses debian:bookworm-slim with libgnutls30 purged (shared libraries and dpkg metadata removed), eliminating all 6 Trivy CVEs while keeping the glibc and ONNX Runtime dependencies required for neural inference. The lite image is true distroless (gcr.io/distroless/static-debian12:nonroot) — zero OS packages, zero CVEs, ~10 MB. Both targets include a built-in --health-check flag for Docker HEALTHCHECK (no wget/curl needed). Multi-arch builds support both linux/amd64 and linux/arm64.
AegisGate MCP includes the same CharCNN-BiLSTM v15 neural model used by AegisGate Platform and Rampart — vendored with zero external module dependencies. The model provides:
| Flag | Env Var | Default | Description |
|---|---|---|---|
--ml | MCP_ML_ENABLED | false (CLI) / true (Docker) | Enable neural threat detection |
--ml-shadow | MCP_ML_SHADOW | false | Log predictions but never block |
--ml-threshold | MCP_ML_THRESHOLD | 0.50 | Threat score threshold (0.0–1.0) |
--ml-model | MCP_ML_MODEL | ./models/threat_cnn_bilstm.onnx | Path to ONNX model file |
AegisGate MCP can be embedded as a Go library:
package main
import ( "context" "log" mcp "github.com/aegisgatesecurity/aegisgate-mcp" )
func main() { cfg := mcp.DefaultServerConfig() cfg.AuthToken = "my-secret-token" cfg.AuditLogPath = "/var/log/mcp-audit.json" cfg.RateLimitRPM = 120 cfg.ScanResponses = true
server, err := mcp.NewSecuredMCPServer(cfg) if err != nil { log.Fatal(err) }
// Register a custom tool // Note: tools are automatically scanned for prompt-injection poisoning // at registration time. If the description or inputSchema contains // malicious patterns, RegisterTool returns *ToolPoisoningError. server.RegisterTool("my_tool", "Does something useful", 40, map[string]interface{}{ "type": "object", "properties": map[string]interface{}{ "param1": map[string]interface{}{"type": "string"}, }, "required": []interface{}{"param1"}, }) server.RegisterToolHandler("my_tool", func(ctx context.Context, params map[string]interface{}) (interface{}, error) { return "result", nil })
// Register a resource (MCP resources/list, resources/read) server.RegisterResource("config://app/info", "App Info", "App config as JSON", "application/json", func(ctx context.Context, uri string) (*mcp.ResourceContent, error) { return &mcp.ResourceContent{URI: uri, Text: {"version":"1.0"}, MimeType: "application/json"}, nil })
// Register a prompt (MCP prompts/list, prompts/get) server.RegisterPrompt("code_review", "Generate a code review prompt", []mcp.PromptArgument{{Name: "filename", Required: true}}, func(ctx context.Context, args map[string]string) (*mcp.GetPromptResult, error) { return &mcp.GetPromptResult{ Messages: []mcp.PromptMessage{{Role: "user", Content: "Review " + args["filename"]}}, }, nil })
// Load built-in policy rules server.LoadDefaultPolicies()
// Start the server if err := server.Start(context.Background()); err != nil { log.Fatal(err) } defer server.Stop() }
See examples/simple-server/ for a complete working example that registers a tool, resource, and prompt.
Reload the neural threat detection model at runtime without restarting the server:
// Swap to a new ONNX model file (verifies SHA-256 hash)
err := server.ReloadMLModel("/path/to/new_model.onnx") if err != nil { log.Printf("model reload failed: %v", err) }
All tools registered via RegisterTool() are automati
只显示了开头部分;其余内容请在仓库中阅读