"GitHub Actions" matching MCP servers:

Enables AI clients to audit GitHub repositories for Dependabot, code scanning, and secret scanning alerts, generate conservative remediation plans, and execute verified fixes through MCP tools with fail-closed mutation controls.

This MCP server enables users to sign in with GitHub and use AI agents to scan entire repositories for leaked secrets such as API keys, passwords, and tokens, delivering a report with the exact file and line plus remediation guidance.

Free deterministic security scan of a public git repository (GitHub, GitLab, Codeberg, Bitbucket): vulnerable dependencies via OSV.dev, secret patterns, and config lint, returned as structured JSON. Tools: scan_repository(url), audit_pricing(). Runs locally over stdio (python3 web/mcp_stdio.py or the Dockerfile) and is also hosted at https://project-feldspar.com/mcp. MIT licence, stdlib-only. Buil

Enables LLMs to access realtime CVE intelligence aggregated from NVD, CISA KEV, EPSS, GitHub advisories, PoC discovery, and Metasploit/Nuclei tooling, providing vulnerability details, exploitation signals, and prioritized triage verdicts.

Provides security audit primitives for MCP servers, agent tool schemas, and system prompts, along with pentest utilities like JWT inspection and HTTP diffing.

Enables AI agents to drive live Hack The Box labs through the real HTB Labs API — spawning, resetting and extending machines, submitting user and root flags with difficulty ratings, browsing challenges, and switching or downloading VPN configurations for the authenticated account. Every call hits the live API rather than cached content, with destructive actions annotated so hosts can gate them behind consent.

Reduces thousands of security findings to the smallest set of high-impact remediation actions, with fail-closed safety gates, typed execution plans, and verification that refuses false all-cleans.

Enables agents and CI pipelines to audit MCP servers and agent tool-chains by statically scanning repositories, local checkouts, tools/list exports, or live endpoints for risks such as destructive actions without confirmation, mismatched safety annotations, injection surfaces, credential or PII exposure, and unguarded command, path, or URL sinks. All checks are read-only and never execute the scanned code or call tools/call.

Connects Claude Code to a Latent Defense deployment to map GitHub repositories into an infrastructure graph, discover attack paths using the JEPA energy model, and triage findings from the terminal.

Enables MCP-capable LLM agents to control YADS queues, manage tags, and trigger scans through YADS's API-authenticated /api/v1 interface without dashboard access. All actions respect tenant isolation and scan limits.

Provides AI agents with structured access to the OWASP Bug Logging Tool (BLT) ecosystem for logging bugs, triaging issues, and managing security workflows. It enables actions like submitting vulnerabilities, tracking contributor leaderboards, and awarding gamified bacon points through a unified interface.

Enables deterministic security testing of AI agents that use tools by serving synthetic MCP environments with poisoned data, fake secrets, and privileged actions. Records agent tool calls and evaluates security invariants (e.g., canary leaks, forbidden access, approval binding) without an LLM judge or real systems.

Enables AI agents to query and act on Microsoft Defender XDR incidents, alerts, advanced hunting data, Entra ID logs, threat indicators, device response actions, and vulnerability management via Microsoft Graph and Defender for Endpoint APIs.

Scan-as-a-Service for MCP servers. Wraps the compuute-scan static security scanner with HTTP and MCP endpoints to analyze public GitHub repos for MCP-specific vulnerabilities.

Enables an AI agent to perform authorized penetration testing through raw HTTP interaction, Python scripting, and shell commands, while providing an authorization wrapper to keep actions within an approved engagement context.

A proof-of-concept tool that integrates AI into security operations, allowing users to perform offensive security tasks like network scanning and reconnaissance through natural language commands to GitHub Copilot.

An MCP server for agent authorization that tests the full effect surface and enforces control over consequential actions before dispatch, emitting verifiable execution evidence.

MCP server that integrates with ARXsec.io API to execute security scans, compliance checks, secrets management, and remediation actions with policy enforcement, audit logging, and human approval workflows.

AI-powered security scanner for Python projects and GitHub repositories. Detects vulnerabilities, secrets, and provides AI risk assessment.

An MCP server for AI security analysis, enabling vulnerability scanning, sensitive information leak detection, and GitHub code leak monitoring via 48 tools.