"Information about Python (programming language or general information)" matching MCP servers:

Provides access to Shodan API functionality, enabling AI assistants to query information about internet-connected devices for cybersecurity research and threat intelligence.

Provides Claude with access to Shodan for IP address lookups, service discovery, and vulnerability scanning, allowing users to query information about hosts, count results, and check API usage.

A Model Context Protocol server that enables AI assistants to search and retrieve information about security exploits and vulnerabilities from the Exploit Database, enhancing cybersecurity research capabilities.

Enables scanning of Claude Code skills, plugins, or MCP servers for malware before installation via static analysis.

A read-only MCP server for the Qualys PCI Merchant API that lets LLM assistants answer questions about PCI compliance posture, such as which hosts are failing PCI or listing high findings.

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.

MCP server for Android APK triage, providing tools to parse APK headers, list DEX classes, and decode AndroidManifest.xml using apktool or androguard backends.

Enables coding agents to perform network diagnostics and lookups, including subnet calculations, port and MAC vendor information, DNS and blocklist checks, TLS certificate inspection, and public IP discovery, all without needing an account or sending telemetry.

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.

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.

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.

Enables querying MITRE's Common Weakness Enumeration database for vulnerability information, supporting CWE lookup, search, taxonomy navigation, and relationship mapping through MCP.

Enables users to retrieve and display CVE vulnerability information from the National Vulnerability Database (NVD) with support for keyword search and detailed lookup.

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.

A security gate MCP server that audits agent extensions (skills, MCP servers, tools) by scanning for risks, adversarial analysis, and sandbox execution, returning a trust verdict of allow, quarantine, or block.

MCP server that exposes 31 OSINT checks from Lissy93/web-check as tools for website analysis, including SSL, DNS, headers, WHOIS, and security presets. Enables natural-language-driven web recon and health checks.

MCP server wrapping Drozer for LLM-driven Android IPC security testing, enabling autonomous enumeration and exploitation of app components via natural language.

A real security scanning MCP server for medical information systems, supporting port scanning, vulnerability detection, medical system identification, and compliance report generation.

Enables security inspection of MCP tool metadata by analyzing tool names, descriptions, and input schemas, and returning SAFE, REVIEW, or HIGH RISK verdicts through the analyze_tools tool.

Enables LLMs to conduct passive attack-surface research by collecting public information, referencing saved reports, and verifying evidence through MCP tools.