SML Risk Firewall
Pre-trade risk checks for agent trades: orders vs your limits, signed receipts.
作者提供的说明(英文原文)
Security co-pilot for AI agents. Scan for vulnerabilities, audit MCP servers, verify governance.
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。
INKOG_API_KEY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 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"inkog": {
"command": "npx",
"args": [
"-y",
"@inkog-io/mcp"
],
"env": {
"INKOG_API_KEY": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add inkog --env INKOG_API_KEY=your-value -- npx -y @inkog-io/mcp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": {
"inkog": {
"command": "npx",
"args": [
"-y",
"@inkog-io/mcp"
],
"env": {
"INKOG_API_KEY": "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": {
"inkog": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@inkog-io/mcp"
],
"env": {
"INKOG_API_KEY": "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7日
注册名称已通过 GitHub 账户 inkog-io 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。
你需要填写:INKOG_API_KEY
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(1.0.20)于8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。你的电脑上还需要有 Node.js。
同一分类中有:SML Risk Firewall, ipdata MCP by usefulapi, MaxMind minFraud MCP by usefulapi
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
Pre-trade risk checks for agent trades: orders vs your limits, signed receipts.
Look up location, network, company and threat data for IP addresses and ASNs in ipdata.
MCP server for MaxMind minFraud — score transactions for fraud risk from your AI assistant.
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。
Security companion for AI agent development in Claude, Cursor, and Claude Code.
Ask your AI pair-programmer to build an agent. Inkog checks it as you code — scanning for vulnerabilities, explaining findings in plain English, verifying AGENTS.md governance, and auditing agent-to-agent delegation. All inside the same conversation, no context switch.
Available in Claude Desktop, Cursor, Claude Code, ChatGPT, and any MCP-compatible client.
Inkog is designed to live inside the conversation where you build the agent — not as a post-hoc gate:
"Scan this with Inkog and show me any CRITICAL or HIGH findings.""Explain the top finding. What's the risk, and how do I fix it?""Verify my AGENTS.md against the code" and "Audit the agent-to-agent delegation".Read the full walkthrough: Building Secure AI Agents with Claude Code and the Inkog MCP.
inkog-io/inkog@v1 to GitHub Actions for automated security gates on every PRAdd to your claude_desktop_config.json:
{
"mcpServers": { "inkog": { "command": "npx", "args": ["-y", "@inkog-io/mcp"], "env": { "INKOG_API_KEY": "sk_live_your_api_key" } } } }
Add to your Cursor MCP settings:
{
"mcpServers": { "inkog": { "command": "npx", "args": ["-y", "@inkog-io/mcp"], "env": { "INKOG_API_KEY": "sk_live_your_api_key" } } } }
npm install -g @inkog-io/mcp
INKOG_API_KEY environment variable| Tool | Description |
|---|---|
inkog_scan | Static analysis for logic flaws and security risks |
inkog_verify_governance | Validate AGENTS.md declarations match actual code behavior |
| Tool | Description |
|---|---|
inkog_compliance_report | Generate EU AI Act, NIST, OWASP compliance reports |
inkog_explain_finding | Get detailed remediation guidance for findings |
inkog_audit_mcp_server | Audit any MCP server before installation |
inkog_generate_mlbom | Generate ML Bill of Materials (CycloneDX, SPDX) |
| Tool | Description |
|---|---|
inkog_audit_a2a | Audit Agent-to-Agent communications |
Static analysis for AI agent code - finds logic flaws and security risks.
Arguments:
path (required) File or directory path to scan policy (optional) Analysis policy: low-noise, balanced, comprehensive, governance, eu-ai-act output (optional) Output format: summary, detailed, sarif
Example: "Scan my LangChain agent for logic flaws"
Validate that AGENTS.md declarations match actual code behavior. This is Inkog's unique differentiator - no other tool does governance verification.
Arguments:
path (required) Path to directory containing AGENTS.md and agent code
Example: "Verify my agent's governance declarations"
Generate compliance reports for regulatory frameworks.
Arguments:
path (required) Path to scan framework (optional) eu-ai-act, nist-ai-rmf, iso-42001, owasp-llm-top-10, all format (optional) markdown, json, pdf
Example: "Generate an EU AI Act compliance report for my agent"
Get detailed explanation and remediation guidance for a security finding.
Arguments:
finding_id (optional) Finding ID from scan results pattern (optional) Pattern name (e.g., prompt-injection, infinite-loop)
Example: "Explain how to fix prompt injection vulnerabilities"
Security audit any MCP server from the registry or GitHub.
Arguments:
server_name (optional) MCP server name from registry (e.g., "github", "slack") repository_url (optional) Direct GitHub repository URL
Example: "Audit the GitHub MCP server for security issues"
Generate a Machine Learning Bill of Materials listing all AI components.
Arguments:
path (required) Path to agent codebase format (optional) cyclonedx, spdx, json include_vulnerabilities (optional) Include known CVEs (default: true)
Example: "Generate an MLBOM for my AI project"
Audit Agent-to-Agent communications for security risks.
Arguments:
path (required) Path to multi-agent codebase protocol (optional) a2a, crewai, langgraph, auto-detect check_delegation_chains (optional) Check for infinite loops (default: true)
Example: "Audit my CrewAI multi-agent system for security risks"
Inkog works with all major AI agent frameworks:
All configuration is done via environment variables:
| Variable | Description | Default |
|---|---|---|
INKOG_API_KEY | Your API key (required) | - |
INKOG_API_URL | API base URL | https://api.inkog.io |
INKOG_API_VERSION | API version | v1 |
INKOG_API_TIMEOUT | Request timeout (ms) | 30000 |
INKOG_LOG_LEVEL | Log level | info |
INKOG_LOG_FORMAT | Log format (json/text) | json |
# Install dependencies
npm install
npm run build
npm run dev
npm test
npm run lint
Most AI agent security tools run after the code is written. Inkog lives inside the conversation where you build the agent — so findings get fixed before they land in a PR, not three weeks later.
Inkog is the only tool that can validate your agent's governance declarations against its actual code behavior. This is essential for:
Unlike traditional code scanners (Snyk, Semgrep, SonarQube), Inkog understands AI-specific issues:
Inkog's Universal IR (Intermediate Representation) works with any agent framework. Add one integration, get analysis for all frameworks.
Apache-2.0 - see LICENSE
Built with security by Inkog.io