"How to update and manage private GitHub repositories (committing and pushing changes)" 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.

Wraps Kali Linux penetration testing tools for authorized security assessments, driven by a local LLM via LM Studio.

This server enables AI agents to delegate GitHub pull request diffs for automated security auditing, returning structured vulnerability and architecture feedback while routing requests through a resilient multi-provider fallback pipeline.

Exposes AI-augmented network reconnaissance and evasion capabilities as callable FastMCP tools, enabling natural language orchestration of host discovery, service fingerprinting, CVE mapping, and attack chain synthesis.

Private MCP server that enables a single GitHub identity to run Codex Security CLI scans on registered repositories, with OAuth authentication and a web-based cockpit UI.

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

Self-hosted MCP engine for private code reviews, providing deterministic static analysis and AST-level search over diffs, with findings passed to a review agent of your choice.

Enables bug bounty hunters to browse programs, inspect scope details, track scope changes over time, and receive personalized, recency-boosted program recommendations based on their skill profile.

A Model Context Protocol (MCP) server for interacting with the Intigriti bug bounty platform's Researcher API. It enables AI assistants to manage bug bounty programs, submissions, and research workflow.

Enables AI assistants to scan websites, public repositories, and OpenClaw/CLAW skills for security vulnerabilities, including local skill-package analysis before installation, cloud scans, and remediation guidance.

Enables interaction with the APVISO AI-powered penetration testing platform to manage targets, initiate scans, and retrieve vulnerability findings. It allows developers to integrate security testing workflows directly into MCP-compatible tools like Claude Code and Cursor.

MCP server that wraps the Frida dynamic instrumentation toolkit, allowing users to attach to processes, hook functions, enumerate modules and exports, and manage scripts through natural language.

A Model Context Protocol (MCP) server for the YesWeHack bug bounty platform that lets Claude query private and public programs, reports, and the hacktivity feed directly from a conversation.

Enables AI assistants to natively execute and manage 600+ Kali Linux security, penetration testing, and forensic tools, including search, help documentation, structured scanners, and workspace management.

Exposes Burp Suite's REST API to AI assistants, enabling users to trigger vulnerability scans, monitor progress, and manage security tasks through natural language. It also provides programmatic access to Burp's security knowledge base for querying vulnerability definitions and remediation advice.

Integrates with Dradis Pro to manage projects, vulnerabilities, content blocks, and document properties through MCP-enabled tools.

A comprehensive MCP server for Frida dynamic instrumentation, enabling AI agents to manage devices, processes, scripts, memory, and ADB operations.

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.