"Understanding Project Planning and Roles" matching MCP servers:

MCP server providing diagnostic tools to analyze software architecture, security, REST API compliance, and dependencies for multiple programming languages. Enables AI agents to run scans and audits on codebases.

Enables autonomous AI agents and penetration testers to conduct authorized security audits with persistent cross-session memory, zero-trust secret scrubbing, dynamic OWASP/ASVS checklists, and hallucination-free exploit PoC generation from captured traffic.

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 MCP clients to work with DefAudit, supporting project and scan listing, starting scans, retrieving results, and marking or unmarking false positives.

AI-powered penetration testing reasoning engine (MCP server) for attack path planning, step scoring, and tool recommendations using Beam Search and Monte Carlo Tree Search.

Enables testing API authentication and authorization by probing endpoints with and without Authorization headers, suggesting auth test matrices for roles, and showing current test configuration.

Enables security auditing, penetration testing, and compliance validation with tools like Semgrep, Trivy, Gitleaks, and OWASP ZAP. Features strict project boundary enforcement and supports OWASP, CIS, and NIST compliance frameworks.

An AI-powered penetration testing reasoning engine that provides automated attack path planning, step-by-step guidance for CTFs/HTB challenges, and tool recommendations using Beam Search and MCTS algorithms.

Enables reverse engineering and binary analysis using Ghidra, YARA, Radare2, and other tools, plus backend development assistance like project analysis, security scanning, and scaffolding.

Integrates Snyk security scanning with MCP clients like Claude Code, enabling listing of projects, querying issues by severity, and filtering by project or scope.

Enables LLM-driven security assessments by exposing Kali tools like nmap, httpx, sqlmap, and ffuf as MCP tools, with explicit planning, parallel tool calls, tiered memory, MITRE ATT&CK mapping, and human approval gates for intrusive operations.

Enables AI assistants to drive OWASP ZAP for authorized penetration testing and bug-bounty workflows, including authenticated scans and vulnerability triage through 67 curated safety-gated tools.

Enables MCP-compatible AI applications to perform read-only npm package and project dependency safety scans, returning proceed, caution, or block verdicts without executing package code.

Standalone MCP server that provides security scanning, project mapping, and vulnerability fix generation to AI coding assistants.

Enables AI agents to orchestrate 100+ security tools over MCP for authorized penetration testing, including recon, scanning, exploitation, attack-chain planning, and knowledge-base retrieval.

A proof-of-concept MCP server for security research demonstrating a multi-phase parasitic attack that disguises itself as a legitimate project memory tool while profiling users and executing cross-server shadowing attacks.

A local Python MCP server for safe, human-led bug bounty recon, providing lightweight helpers for scope checks, headers, robots.txt, sitemap.xml, JavaScript URL collection, endpoint extraction, URL deduplication, evidence notes, and manual test planning.

Enables automated penetration testing workflow planning using Beam Search and Monte Carlo Tree Search algorithms to generate step-by-step attack paths, score vulnerabilities, and recommend tools for reconnaissance, exploitation, and privilege escalation tasks.

Enables AI agents to control and analyze RFID hardware through natural language: read, crack, emulate, and clone cards via MCP tools, with safety gates, offline dump analysis, and a host-side card library.

Enables AI assistants to perform Volatility 3 memory forensics through natural language, including process and network analysis, injection detection, and shellcode extraction from memory dumps.