"Technology pre-research resources" matching MCP servers:

This local MCP server keeps vulnerability intelligence, research scope, scanner results, evidence receipts, Bugcrowd VRT assessments, and report drafts in one SQLite ledger. It is built for authorized defensive research and does not scan, exploit, or submit reports.

Free deterministic security scan of a public git repository (GitHub, GitLab, Codeberg, Bitbucket): vulnerable dependencies via OSV.dev, secret patterns, and config lint, returned as structured JSON. Tools: scan_repository(url), audit_pricing(). Runs locally over stdio (python3 web/mcp_stdio.py or the Dockerfile) and is also hosted at https://project-feldspar.com/mcp. MIT licence, stdlib-only. Buil

A local-first MCP attack kit for authorized security research and red teaming, demonstrating exfiltration, agent manipulation, and other abuse patterns via pluggable cases.

Enables MCP clients to drive the complete mobile security toolkit—static/dynamic analysis, Frida hooks, runtime exploration, traffic interception, network setup, and IoT scans—through engine-exposed tools.

Enables Android APK reverse engineering and Flutter runtime injection through a six-step pipeline of decompile, analyze, synthesize, inject, patch, and repackage. Provides MCP tools for authorized security research and penetration testing.

Enables AI assistants to search and analyze vulnerabilities and exploits from multiple intelligence sources, including NVD, CISA KEV, ExploitDB, Metasploit, and more, with tools for CVE research, exploit analysis, and report generation.

MCP server that provides AI-native access to BeVigil's OSINT API, enabling mobile app security research and asset discovery through tools for hosts, subdomains, S3 buckets, URLs, wordlists, and multi-step investigations.

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.

MCP server for auditing infrastructure-as-code attack paths, finding multi-hop chains from public internet to sensitive resources.

Connects MCP clients to pre-submission review that argues against a draft bug-bounty report or smart-contract finding the way a triager would, tying every claim to a supplied file and line and returning a submit, rewrite-then-submit, prove-first, hold-duplicate or drop verdict. Exposes tools to list review profiles, prepare reviews for the agent's own model, build hash-verified review packets, and — with a connection token — run hosted profiles on your own provider key.

A Model Context Protocol (MCP) server for interacting with the Intigriti bug bounty platform's Researcher API. It enables AI assistants to manage bug bounty programs, submissions, and research workflow.

Enables AI agents to orchestrate security research workflows by connecting to containerized security tools via MCP, allowing automated vulnerability analysis and pipeline execution.

Enables MCP-native multi-agent security audits for Google Antigravity, orchestrating subagents for 0day research, static analysis, PoC verification, exploit chaining, reporting, and code remediation.

Security scanning for AI coding tools (Claude Code, Cursor, Windsurf) including secrets detection, MCP config vulnerabilities, agent instruction checks, threat modeling, prompt injection testing, pre-commit security checks, and dependency vulnerability scanning.

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

Enables developers and security teams to run evidence-first Android and iOS security audits, manage jobs and reports, query public vulnerability intelligence, evaluate policies, and plan runtime checks through stdio MCP tools and resources.

GDB MCP server for binary security research (reverse engineering / PWN) with first-class pwndbg integration, enabling heap analysis, cyclic pattern, checksec, ROP gadgets, and more via MCP protocol.

An MCP server that enables AI-assisted mobile security testing by exposing Frida functionality for Android application research. It provides tools for hooking Java methods, manipulating memory, managing device processes, and executing custom Frida scripts.

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

A security research MCP server for testing tool call safety with deterministic policies like allowlists, path boundary enforcement, SSRF prevention, output redaction, and prompt injection detection, without requiring external LLMs or API keys.