Overview: LOVI MCP Product Announcement for AI-Powered Security
LOVI MCP (Loginsoft Vulnerability Intelligence MCP) is a Model Context Protocol server that brings real-time vulnerability intelligence into AI assistants like ChatGPT, Claude, Gemini, Microsoft Copilot, and any MCP-compatible AI agent. By combining LOVI’s live CVE, malware, and threat of actor data with the reasoning power of leading LLMs, security teams can move from manual research to AI-driven, risk-based decisions in seconds.
Key Takeaways: LOVI MCP Real-Time Vulnerability Intelligence
- LOVI MCP connects AI assistants to live vulnerability intelligence, including threat scores, active exploitation telemetry, malware associations, and CISA KEV data, not just static CVE fields.
- The Model Context Protocol (MCP), now governed by the Linux Foundation, makes LOVI MCP portable across ChatGPT, Claude, Gemini, Copilot, and custom AI agents without vendor lock-in.
- LOVI MCP real-time vulnerability intelligence accelerates workflows for SOC, vulnerability management, threat intelligence, and DevSecOps teams by shrinking research time from hours to seconds.
What is LOVI?
LOVI (Loginsoft Vulnerability Intelligence) is our comprehensive vulnerability intelligence platform that aggregates, enriches, and correlates CVE data from multiple sources to deliver actionable security insights. LOVI provides:
| Capability |
Description |
| AI-Powered Threat Scores |
Nuanced scoring with evidence and justification for prioritization |
| Pre-NVD Intelligence |
Early warning on vulnerabilities before NVD publication |
| Live Exploitation Data |
Real-time sensor telemetry showing CVEs being actively exploited |
| Malware Correlation |
CVE-to-malware and threat actor mapping with MITRE ATT&CK TTPs |
| CISA KEV Integration |
Known Exploited Vulnerabilities catalog with remediation deadlines |
| OSS Vulnerability Tracking |
Coverage across npm, PyPI, Maven, Go, and other ecosystems |
| Trending/Emerging CVEs |
Social media and security community intelligence aggregation |
What is the Model Context Protocol (MCP)?
The Model Context Protocol (MCP) is an open standard introduced by Anthropic and is now governed by the Linux Foundation. MCP standardizes how AI systems - including Large Language Models (LLMs) - connect with external data sources, tools, and APIs.
Think of MCP as a universal adapter that allows AI assistants to access external capabilities. Just as browser extensions add features to your browser, MCP servers add capabilities to your AI. Major AI platforms now support MCP:
| AI Platform |
MCP Support |
| OpenAI ChatGPT |
Desktop app, Agents SDK, and API integrations |
| Anthropic Claude |
Claude.ai, Claude Desktop, and API |
| Google Gemini |
Agent Development Kit (ADK) with MCPToolset |
| Microsoft Copilot |
Copilot Studio, Azure OpenAI, Semantic Kernel |
| Custom AI Agents |
LangChain, LlamaIndex, AutoGen, CrewAI, and more |
Who Benefits from LOVI MCP?
LOVI MCP is designed for four key personas in the cybersecurity ecosystem. Each can leverage AI-powered vulnerability intelligence in unique ways to enhance their workflows and outcomes.
PERSONA 1: SOC ANALYST / INCIDENT RESPONDER
The Challenge: SOC analysts face alert fatigue and need rapid context on CVEs during active incidents. Manually researching each vulnerability wastes critical response time.
How LOVI MCP Helps:
Example Prompts:
| Ask Your AI Assistant |
LOVI MCP Response |
| Is CVE-2025-55182 being actively exploited? Are there any malware families using it? |
Returns threat score (99), EPSS (50.5%), confirms active exploitation, lists 6 malware families (MINOCAT, SNOWLIGHT, HISONIC, etc.), and 4 threat actors |
| Show me all CVEs from today's alerts that have CISA KEV entries and active malware associations |
Batch checks multiple CVEs, returns prioritized list with KEV status, malware counts, and threat actor associations |
| What are the TTPs for the malware associated with this vulnerability? I need to build detection rules. |
Returns MITRE ATT&CK techniques, tactics, targeted industries, and aggregated TTPs across all associated malware |
| Get me live exploitation telemetry for the past 24 hours |
Returns CVEs observed in active scanning/exploitation with attacker IPs, attack counts, and timestamps |
Outcome: Reduce mean-time-to-understand (MTTU) from hours to seconds. Make data-driven decisions on incident priority and response actions.
PERSONA 2: VULNERABILITY MANAGER / RISK ANALYST
The Challenge: Thousands of CVEs are published annually. Prioritizing which vulnerabilities to patch first requires understanding real-world risk, not just CVSS scores.
How LOVI MCP Helps:
Example Prompts:
| Ask Your AI Assistant |
LOVI MCP Response |
| Find all critical vulnerabilities affecting Apache Tomcat in our environment |
Searches by CPE/product name, returns paginated CVE list with threat scores, EPSS, exploit availability, and malware flags |
| Which CVEs added to CISA KEV this month have remediation deadlines in the next 2 weeks? |
Queries CISA KEV catalog filtered by date range, returns CVEs with due dates, products affected, and remediation priorities |
| Compare the risk of these 10 CVEs from our scan results - which should we patch first? |
Batch checks all CVEs, returns comparative analysis with threat scores, exploitation status, malware associations, and prioritized ranking |
| Show me trending vulnerabilities in the security community this week |
Returns emerging CVEs from Twitter, GitHub, Reddit, and security blogs with trending counts and threat intelligence |
Outcome: Move from CVSS-based prioritization to risk-based prioritization. Focus remediation efforts on vulnerabilities that pose actual threat to your organization.
"
A Message from Our CTO
Today, I am thrilled to announce the release of LOVI MCP - a Model Context Protocol server that brings Loginsoft Vulnerability Intelligence directly into the AI tools you already use.
The cybersecurity landscape is evolving faster than ever. With thousands of CVEs published annually, active exploitation happening within hours of disclosure, and threat actors rapidly weaponizing vulnerabilities, security teams need intelligence that moves at the speed of threats - not the speed of manual research.
LOVI MCP solves a fundamental problem: AI assistants are powerful, but they lack real-time security context. By integrating LOVI with the Model Context Protocol, we enable any MCP-compatible AI platform - including ChatGPT, Claude, Gemini, Microsoft Copilot, and custom AI agents - to access live vulnerability intelligence, threat actor data, malware associations, and actionable security insights.
This is not just another integration. This is about empowering security professionals to work smarter, faster, and with greater precision by combining the analytical power of AI with the real-time intelligence of LOVI.
"
PERSONA 3: THREAT INTELLIGENCE ANALYST
The Challenge: Tracking threat actor campaigns, malware evolution, and vulnerability weaponization requires aggregating intelligence from dozens of sources and correlating complex relationships.
How LOVI MCP Helps:
Example Prompts:
| Ask Your AI Assistant |
LOVI MCP Response |
| What malware campaigns have been active in the last 30 days? Which CVEs are they exploiting? |
Returns malware timeline with families, APT groups, campaigns observed, and associated CVEs |
| Give me the full threat profile for Earth Lamia including TTPs, targets, and CVEs they exploit |
Returns detailed MITRE ATT&CK techniques, targeted industries/countries, associated CVEs, and researcher notes |
| Get TTPs for all malware families associated with CVE-2025-55182 so I can build comprehensive detection coverage |
Batch retrieves threat profiles for all associated malware, aggregates TTPs by usage frequency, provides detection coverage summary |
| Are there any Pre-NVD vulnerabilities I should be tracking before they go public? |
Returns Pre-NVD CVEs observed before official NVD publication - early warning intelligence for proactive defense |
Outcome: Produce actionable threat intelligence reports in minutes instead of days. Track adversary evolution and anticipate their next moves.
PERSONA 4: SECURITY ENGINEER / DEVSECOPS
The Challenge: Securing the software supply chain requires visibility into OSS vulnerabilities across multiple ecosystems. Engineers need to quickly assess risk in dependencies and third-party components.
How LOVI MCP Helps:
Example Prompts:
| Ask Your AI Assistant |
LOVI MCP Response |
| What are the trending OSS vulnerabilities in the npm ecosystem this week? |
Returns trending npm vulnerabilities useful for SCA and dependency security prioritization |
| Show me the OSS vulnerability database for PyPI packages in our requirements.txt |
Returns OSS-specific vulnerabilities across PyPI ecosystem with severity and remediation guidance |
| Are there any vulnerabilities in React 19.x that we should be concerned about? |
Searches by product/version, returns CVEs like React2Shell (CVE-2025-55182) with full context on exploitation and patches |
| Give me OSS ecosystem insights - which package managers have the most critical vulnerabilities right now? |
Returns high-level vulnerability trends across Maven, npm, PyPI, Go, RubyGems, crates.io, NuGet, and more |
Outcome: Shift security left with real-time OSS intelligence. Make informed decisions about dependencies before they become production vulnerabilities.
LOVI MCP: Complete Capability Reference
The following tools are available through LOVI MCP for any AI assistant or agent that supports the Model Context Protocol:
| MCP Tool |
Description & Use Case |
| lovi_search_cve |
Get comprehensive intelligence for a specific CVE: threat score, CVSS, EPSS, exploit availability, malware associations, CISA KEV status, patches, and MITRE ATT&CK mappings |
| lovi_batch_check_cves |
Check multiple CVEs in parallel for malware/exploit associations. Much faster than individual lookups. Returns summary with threat scores, malware counts, and KEV status |
| lovi_search_by_cpe |
Find CVEs affecting a specific product or platform. Accepts CPE strings or natural language ("Windows 10", "Apache Log4j 2.14") |
| lovi_get_cisa_kev |
Query CISA Known Exploited Vulnerabilities catalog for federal compliance tracking. Filter by CVE, product, date added, or due date |
| lovi_get_emerging |
Get trending/emerging CVEs from Twitter, GitHub, Reddit, and security blogs. Great for threat hunting and proactive detection development |
| lovi_get_prenvd |
Get Pre-NVD CVEs — vulnerabilities observed before official NVD publication. Early warning for emerging threats |
| lovi_get_live_intel |
Real-time sensor telemetry of CVEs being actively scanned/exploited in the wild. Includes attacker IPs, attack counts, timestamps |
| lovi_get_malware_timeline |
Get recent malware campaigns and threat actor activity. Track malware families, APT groups, and campaigns over specified timeframe |
| lovi_get_threat_profile |
Get MITRE ATT&CK TTPs for a malware family or threat actor. Returns techniques, targeted countries/industries, associated CVEs, and researcher notes |
| lovi_batch_get_threat_profiles |
Get TTPs for multiple threats in parallel. Aggregates techniques across all threats for comprehensive detection coverage |
| lovi_get_oss_collection |
Query OSS vulnerability database across ecosystems: Maven, npm, PyPI, Go, RubyGems, crates.io, NuGet, Android, Packagist, Debian |
| lovi_get_oss_trending |
Get trending OSS vulnerabilities by ecosystem. Useful for SCA and dependency security prioritization |
| lovi_get_oss_insights |
Get high-level OSS ecosystem insights and vulnerability trend analysis across all supported package managers |
| lovi_get_cve_general |
List CVEs by date range or year. Useful for tracking new disclosures, quarterly reporting, or historical analysis |
Getting Started with LOVI MCP
LOVI MCP is designed for easy integration with any MCP-compatible AI platform. Here's how to get started:
For ChatGPT, Claude, Gemini, and Copilot Users
- Obtain LOVI API credentials from your Loginsoft account or contact sales@loginsoft.com
- Configure the LOVI MCP server in your AI platform's MCP settings
- Start asking your AI assistant about vulnerabilities, threats, and security intelligence
- The AI will automatically invoke LOVI tools to retrieve real-time data and provide actionable insights
For Developers Building Custom AI Agents
LOVI MCP integrates seamlessly with popular AI agent frameworks:
| Framework |
Integration Method |
| LangChain |
Use MCP tool integration with LangChain agents |
| LlamaIndex |
Connect via MCP server as external tool provider |
| AutoGen |
Register LOVI MCP tools for multi-agent workflows |
| CrewAI |
Add LOVI capabilities to crew member agents |
| Google ADK |
Use MCPToolset to discover and expose LOVI tools |
| Semantic Kernel |
Microsoft's AI orchestration with MCP support |
Why LOVI MCP?
| Benefit |
Description |
| Real-Time Intelligence |
Unlike static AI training data, LOVI provides live vulnerability intelligence updated continuously |
| Platform Agnostic |
Works with any MCP-compatible AI - no vendor lock-in |
| Actionable Context |
Not just CVE data, but threat scores, malware correlations, TTPs, and remediation guidance |
| Enterprise Ready |
Secure API access, role-based permissions, audit logging |
| Accelerate Workflows |
Reduce research time from hours to seconds across all security functions |
Empower your AI. Secure your enterprise. Move at the speed of threats.
FAQ's of LOVI MCP Real-Time Vulnerability Intelligence
1. What makes LOVI MCP real-time vulnerability intelligence different from traditional CVE feeds?
Traditional CVE feeds provide static identifiers and limited metadata, while LOVI MCP real-time vulnerability intelligence layers threat scores, exploitation telemetry, malware associations, CISA KEV status, and Pre-NVD insights directly into AI workflows.
2. How does LOVI MCP real-time vulnerability intelligence keep data up to date for AI platforms?
LOVI MCP real-time vulnerability intelligence continuously ingests data from advisories, sensor telemetry, CISA KEV, EPSS, social media, and research blogs, exposing the latest state through MCP tools every time an AI assistant queries it.
3. Which AI assistants support LOVI MCP real-time vulnerability intelligence today?
Any assistant built on an MCP-compatible platform can use LOVI MCP real-time vulnerability intelligence, including OpenAI ChatGPT, Anthropic Claude, Google Gemini, Microsoft Copilot, and custom agents built with LangChain, LlamaIndex, AutoGen, CrewAI, and more.
4. How does LOVI MCP real-time vulnerability intelligence help with OSS and supply chain security?
LOVI MCP real-time vulnerability intelligence provides OSS vulnerability collections and trending insights across ecosystems like npm, PyPI, Maven, Go, RubyGems, crates.io, and NuGet, enabling DevSecOps teams to assess and prioritize risks in dependencies.
5. Is LOVI MCP real-time vulnerability intelligence suitable for regulated or enterprise environments?
Yes, LOVI MCP real-time vulnerability intelligence is designed for enterprise deployments, offering secure API-based access, role-based controls, and detailed logging, and can be integrated into existing security tooling and workflows
