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

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

Enables federated multi-source research by fanning out queries across web, community, and social sources, deduplicating and interleaving results, and storing a persistent corpus for cross-checking.

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.

Enables semantic search across personal PDF paper collections with page-level citations, allowing users to query their library from any MCP-capable client.

MCP server that provides a 216-rule, framework-aware Kotlin/JVM security analyzer, enabling AI coding agents to query real security findings while writing code.

A unified MCP server for academic paper discovery, citation exploration, and research intelligence workflows over multiple scientific knowledge sources.

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.

Browser-based research MCP server that drives a real Chromium browser via patched Playwright to access JavaScript-rendered content, dynamic tables, and login-walled dashboards. It provides tools for visiting URLs to extract DOM text and screenshots, and for performing structured data extraction using Anthropic Claude Sonnet.

AI-powered VMware NSX DFW microsegmentation and security. Manage distributed firewall policies, security groups, Traceflow, and IDPS with 20 MCP tools.

A read-only FastMCP server for academic research that lets agents search papers, inspect metadata, follow citation graphs, generate BibTeX, and read full texts of open-access PDFs via semantic scholar, OpenAlex, arXiv, DBLP, and Crossref.

Provides machine learning researchers with tools for creating publication-quality scientific visualizations, statistical plots, and 2D data representations. It streamlines the research workflow by enabling AI assistants to generate complex figures from CSV, JSON, or direct data inputs.

An MCP server exposing a registry of paper-backed quantitative trading methods plus a deterministic, no-LLM decision helper for reproducible trading research.

14 atomic MCP tools for AppSec and AI Security engineers: source/schema/prompt audit primitives, JWT inspect, HTTP diff, pentest atoms (default creds, GraphQL introspect, phpggc, interactsh OOB), and a defensive helpers library that fixes the bugs the detectors flag. SARIF output, PyPI Trusted Publishing with Sigstore provenance.

Enables producing verifiable FORRT nanopublication chains with grounded quote verification and compact Science Live constellation projections, supporting reproduction, replication, and new research workflows.

Provides security audit primitives for MCP servers, agent tool schemas, and system prompts, along with pentest utilities like JWT inspection and HTTP diffing.

Provides comprehensive access to Roam Research's API functionality. This server enables AI assistants like Claude to interact with your Roam Research graph through a standardized interface.

An open-source deep research MCP server that provides multi-source web search and synthesis with citations, enabling agents to perform citation-backed research using Qwen3-30B-A3B-Thinking and other models.

MCP server that acts as a research intelligence agent, converting natural language queries into SQL or full-text search against Hacker News and arXiv data, and returning answers with supporting evidence.

Empowers coding agents for machine learning research by providing access to Lacuna's research map, including novel research proposals, research directions, papers, authors, venues, institutions, and hypotheses. It enables searching and retrieving context-aware research information through MCP tools.

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