Security co-pilot for AI agents. Scan for vulnerabilities, audit MCP servers, verify governance.
Security co-pilot for AI agents. Scan for vulnerabilities, audit MCP servers, verify governance.
Valid MCP server (1 strong, 1 medium validity signals). 5 known CVEs in dependencies (0 critical, 5 high severity) Package registry verified. Imported from the Official MCP Registry.
5 files analyzed · 6 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
This plugin requests these system permissions. Most are normal for its category.
Set these up before or after installing:
Environment variable: INKOG_API_KEY
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-inkog-io-inkog": {
"env": {
"INKOG_API_KEY": "your-inkog-api-key-here"
},
"args": [
"-y",
"@inkog-io/mcp"
],
"command": "npx"
}
}
}From the project's GitHub README.
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
# Build
npm run build
# Run in development mode
npm run dev
# Run tests
npm test
# Lint
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
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