"Research on Threats and Security Risks" matching MCP servers:

Protects AI agents from threats like prompt injection, jailbreaks, and SQL injection through a multi-layer scanning pipeline. It also enables PII redaction and rehydration to ensure data privacy during LLM interactions.

Research methods, workflow tools, and independent review for AI agents, packaged as a Skill, plugin, and local MCP server.

Bridges the ChatGPT web UI to a local development environment over MCP, letting the model read and patch files, run real shell commands and terminals, execute tests, and control the desktop (screen, mouse, keyboard, clipboard) within user-approved folders. It adds parallel workers, goal/loop long-task control, plugin tools, and a security-hardening layer with risk-tiered shell policy, audit logging, and credential sanitization.

Enables autonomous AI agents and penetration testers to conduct authorized security audits with persistent cross-session memory, zero-trust secret scrubbing, dynamic OWASP/ASVS checklists, and hallucination-free exploit PoC generation from captured traffic.

Enables deep research tasks using a multi-agent architecture that integrates any LLM and MCP tools. Available via MCP stdio, streamable HTTP, and SSE transports.

Enables agents to execute structured research runbooks against a 440+ tool data bank and receive reports in which every number traces back to a cited source in an evidence ledger. Exposes tools for launching jobs, listing available runbooks, polling run status, and fetching finished markdown or HTML reports.

Enables AI agents to perform deep web research by searching, fetching, chunking, retrieving, and synthesizing cited answers from exact source passages via a deep_research tool.

Aggregates and routes multiple MCP servers with intelligent tool recommendation and batch parallel execution, enabling unified access and efficient tool usage.

Zero-trust safety & settlement rail for autonomous AI agents. Sub-10ms deterministic guardrails, secret leak defense, bounded wallet controls, and on-chain Proof-of-Safety attestations via x402.

Paid web research MCP tools for autonomous agents: search, page extraction, citations, and diff monitoring through a live x402 API. Unpaid calls return the Base USDC payment requirement so agents can pay and retry safely.

A small local MCP adapter that lets Claude Code delegate bounded research work to Codex plan credits without giving the worker ownership of the final report.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Enables users to create and refine a research outline, queue report generation in the background, and retrieve progress or completed Markdown reports, with automatic checkpointing so unfinished work can resume after a restart.

Implements Anthropic's multi-agent research architecture with subagent spawning, adaptive stopping, and citation processing for automated research.

Enables autonomous web research, file management, and dynamic UI dashboard generation through Gemini LLM and FastMCP.

Exposes web search and page fetching tools via the MCP protocol, allowing integration with AI editors like Cursor for autonomous research workflows.

Enables multi-agent financial research through MCP, combining live or offline market, news, fundamentals, document RAG, and risk tools with critic review, synthesis, and execution tracing.

Provides a hand-written MCP server integrated with a LangGraph agent to benchmark multiple agent topologies and measure their failure rates.

Provides automated security incident remediation tools for AWS, enabling real-time threat response by quarantining malicious S3 objects, restricting IAM access, and updating security groups.

Unifies 7,283+ detection rules from Sigma, Splunk ESCU, Elastic, and KQL into a single queryable interface via MCP, with a web dashboard and autonomous agent pipeline for detection engineering.