"Python" matching MCP servers:

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.

Enables coding agents and CI/CD pipelines to audit untrusted code by detecting Python sandbox escapes, SQL injection taint, ReDoS regex vulnerabilities, and CORS misconfigurations, while generating Seccomp BPF filters for safer execution.

A scope-aware bug-bounty & reconnaissance MCP server that works out of the box on the Python standard library and augments itself with your favourite CLI tools when they're present.

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.

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 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 Python MCP server that decompiles Android APK/XAPK/JAR/AAR files and extracts HTTP APIs used by the app.

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

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

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.

AI-orchestrated security testing via 6 Python tools (recon, port scan, subdomain hunting, frontend scanning, API fuzzing, and nemesis orchestrator) exposed as MCP tools for use by AI agents.

Gives AI agents and LLMs deep, queryable access to a codebase's structure and data flow through Joern Code Property Graphs. Enables running CPGQL queries, tracing data flow and taint, slicing programs, and hunting vulnerabilities across languages like Java, C/C++, JavaScript, Python, Go, and more.

Enables AI agents to scan code for security vulnerabilities before execution, supporting Python and JavaScript/TypeScript with deterministic AST-based analysis and optional Solana micropayments.

Enables MCP-compatible agents to audit an entire repository through one question, detecting stacks and running parallel checks for dead code, dependencies, security, CVEs, complexity, and lint across Laravel/PHP, Python, TypeScript/React, and Flutter/Dart. It returns normalized, severity-sorted findings with false positives flagged and secret values kept out of the output.