"A sandbox environment to run Python code and install dependencies" matching MCP servers:

Enables assistants to analyze files and URLs for malware by integrating with security services like VirusTotal and ANY.RUN, returning threat reports.

Provides 28 MCP tools across 16 analysis engines for comprehensive Python code quality assessment, including complexity scoring, security scanning, dead code detection, dependency auditing, and test quality analysis.

Enables automated security code auditing using LLM and MCP, including AST parsing, taint analysis, dataflow tracing, and automated PoC generation for multi-language codebases.

Multi-language SAST and AI-powered fuzzing MCP server for Claude Code integration, enabling static and dynamic security analysis of code.

MCP server that guides LLM security reviews step-by-step, tracking progress and ensuring all assigned source code is read before completing each plan step.

An AI-native code security audit MCP server that supports multi-language AST analysis, call graph analysis, vulnerability detection, and AI deep audit.

Enables AI-powered automated testing, security scanning, code review, and maintenance tasks directly within Claude Code or desktop.

Enables MCP clients to run security and code review on pull requests and diffs, exposing review_pr and review_diff capabilities with local-first analyzers and LLM explanations.

Code review as an MCP server — structured code quality reviews with OWASP security scanning.

Provides threat intelligence and vulnerability research tools by integrating with NVD, VirusTotal, AbuseIPDB, Shodan, and MITRE ATT\&CK. It enables users to perform CVE lookups, analyze IP reputation, and retrieve detailed MITRE ATT\&CK technique information.

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

Gives AI agents a browser that bypasses bot detection, a MITM proxy for traffic interception, and a Python sandbox to autonomously write and execute security exploits.

An MCP server that provides passive and low-impact active reconnaissance tools for authorized bug bounty and security assessments, enabling LLMs to perform structured recon and generate reports.

A security-focused MCP server that enables AI assistants to search PyPI packages, scan for vulnerabilities, audit dependencies, and ensure security across Python projects.

Autonomous penetration testing powered by a local LLM, automating tool chaining for recon, vulnerability scanning, exploit research, and reporting.

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

Exports vulnerability and asset data from Rapid7 Command Platform via the Bulk Export API into a local DuckDB database, enabling AI assistants to run natural language queries and SQL analysis with sandboxed security.

Agent-native "safe to ship?" security gate for AI-generated code. Uses real parsers and inter-rocedural taint analysis (JS/TS, Python, Go) to flag the classes AI coding agents get wrong — secrets, SQL injection, SS, SSRF, path traversal, command injection, weak JWT/CORS — and ranks findings by confidence. Exposes a scan tool over MCP.

Provides a generic HTTP client tool allowing AI agents to make arbitrary HTTP requests from their environment, with support for environment-variable placeholders for secrets.

MCP server for Cursor that scans codebases for security issues including hardcoded secrets, SAST, vulnerable dependencies, and IaC misconfigurations.