"How to implement intent recognition in MCP" matching MCP servers:

Enables authorized web/API security analysis as a stateful, multi-stage workflow with persistent session state, human-controlled validation, candidate versus confirmed finding tracking, and stop conditions.

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

Enables AI assistants to scan Terraform and Dockerfiles for security misconfigurations, returning structured Checkov findings that can be explained in plain language.

GhostHunt is an MCP server that scans your development machine for API keys, tokens, and credentials hiding in places you forgot to check.

Connects an AI assistant to an already-running mitmweb session so it can read, search, diff, replay, and generate code from the same network flows shown in the UI.

Security scanning for MCP servers from the inside out. Provides runtime inspection, AST-based static analysis, config audit, dependency analysis, and OWASP MCP Top 10 compliance in a single MCP server.

Enables AI assistants to run Kali Linux security tools in an isolated Docker container for tasks like network scanning, port checking, and service enumeration.

Enables Solidity developers and security auditors to decode EVM calldata, pinpoint revert locations in debug traces, calculate storage slot layouts, and scan contracts for reentrancy and Yul assembly issues.

Provides an MCP interface to a full Kali Linux environment running in Docker, enabling AI assistants to execute security tools like nmap, sqlmap, and metasploit. It allows users to start/stop the container, run shell commands, and transfer files for security testing and educational purposes.

Provides AI agents with 37 OSINT tools and 12 data sources to perform unified reconnaissance, domain analysis, and attack surface mapping. It enables agents to query, correlate, and reason across platforms like Shodan, VirusTotal, and Censys in parallel.

Connects AI assistants to AttackForge's Self-Service API with full endpoint coverage, response size optimization, and local caching for efficient use in long conversations.

Enables AI agents to audit web headers and DOM code, API routes, and database queries for vulnerabilities such as XSS, BOLA/IDOR, and SQL/NoSQL injection, returning scored CWE findings. It also automatically synthesizes secure drop-in replacement code with unified git diffs for review.

A self-hostable, vulnerable-by-design MCP server for learning how object-level authorization bugs (BOLA/IDOR) appear in multi-tenant tools.

A deliberately vulnerable MCP server for practicing exploitation of tool poisoning, command injection, and path traversal. Includes fixed versions and an agent demo to reproduce the issues in a controlled environment.

Transforms mitmproxy into a toolset for AI agents to inspect, modify, and replay HTTP/HTTPS traffic in real-time.

Exposes every operation in the ConnectSecure OpenAPI specification as an MCP tool, enabling vulnerability management, assets, assessments, integrations, and reporting.

Enables scanning a single-file Solidity contract before deployment by running Slither, Aderyn, and rug-pull/centralization heuristics in a sandboxed environment, then returning a Deployable / Fix first / Do not deploy verdict with plain-language explanations. Exposes one tool, scan_contract, with a per-caller daily limit.

Enables AI agents to perform pay-per-call security verification of wallets, tokens, contracts, dApps, agents, and more via a remote endpoint with no installation.

Enables running Kali Linux security tools and commands in a containerized environment for semi-automated penetration testing, with background job management and out-of-band interaction detection.

Provides a set of MCP tools to clone and analyze arbitrary MCP server repositories, run static and dynamic security probes in isolated Docker containers, and produce vulnerability verdicts with a human-in-the-loop approval step before filing public reports.