"Multi-Agent Systems with Shared Memory Storage" matching MCP servers:

Extends IDA Pro with multi-instance support and vulnerability scanning for AI-assisted reverse engineering.

Security scanning, prompt injection detection, secret leak detection, and agent permission auditing for AI agent workflows.

Enables security analysts to carry structured investigation state across sessions by storing typed observations, hypotheses, tasks, evidence and versioned decisions in a local SQLite graph with full-text search. It also enforces authorized scope and request controls, redacted and content-hashed evidence, duplicate-test signatures and validation gates that leave findings in draft until reproducibly confirmed, then produces technical and executive reports for Antigravity, Codex and other stdio MCP clients.

Enables management of capture sessions, rules, certificates, and protocol communication through an MCP endpoint, controlling a sing-box core.

Enables coding agents to scan a public URL in passive or authorized mode and receive only bounded, sanitized structured findings (severity, confidence, standard, evidence, remediation) with quarantined evidence instead of raw page dumps. A second tool lets agents inspect the scanner's safety boundaries and coverage without making any network request.

Security scanner for MCP servers. Detects prompt injection, command injection, auth bypass, and excessive permissions across tools, resources, and prompts.

Two-way Burp Suite MCP bridge enabling AI agents to capture traffic, analyze endpoints, queue scans, and send findings back to Burp.

A security scanner for AI coding agents and autonomous assistants that scans code for vulnerabilities, detects hallucinated packages, blocks prompt injection, and provides LLM-powered semantic code review via MCP or CLI.

Enables LLM clients to conduct authorized penetration testing and CTF challenges through a multi-mode agent with evidence-chain anti-hallucination, skill evolution, and MCP tool orchestration.

A model-neutral cyber capability brain for AI agents and human researchers, providing MCP tools for knowledge ingestion, composition, campaign planning, fleet management, evidence binding, and discovery replay.

Enables AI clients to audit GitHub repositories for Dependabot, code scanning, and secret scanning alerts, generate conservative remediation plans, and execute verified fixes through MCP tools with fail-closed mutation controls.

MCP server for AI-powered code security, quality, and performance review. Enables auditing code directly from VS Code via right-click or MCP tools.

Offers a control surface for AI agent security with four independent checks: source-code scanning, tenant isolation, LLM content verification, and deploy gating. Currently in pre-release, with no functional scanning engines yet.

Performs static security analysis of Solana programs and generates x402 payment invoices for automated agent-to-agent audit workflows.

Enables users to query BloodHound Active Directory graph data using natural language, finding attack paths, Kerberoastable accounts, and other AD security insights.

A Codex-style MCP server providing 126 tools to operate a Kali Linux machine from ChatGPT or any compatible MCP client, including shell execution, filesystem operations, Git, Docker, browser automation, and security tool wrappers.

Enables MCP-compatible agents to submit source code for automated SAST/SCA security audits paid via x402 USDC micropayments on Base, returning structured vulnerability findings, CWE IDs, and optional remediated code patches.

Enables AI agents and MCP servers to operate under autonomous security enforcement, including pre-deployment scanning, per-call authorization, runtime monitoring, incident containment, and comprehensive auditing.

Enables passive OSINT reconnaissance by providing search dorking and open-source intelligence collection tools through MCP, without requiring active interaction with target systems.

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.