Nerq AI Agent Ecosystem Weekly Report for Week Ending 2026-04-27
One-Paragraph Summary
This week, Nerq indexed an additional 9,441 agents and tools, bringing the total to 257,686. The ecosystem continues to grow with significant contributions from platforms like PulseMCP and AgentVerse. Key trends include a rise in community-based frameworks and a focus on cybersecurity tools. Panther Labs emerged as this week's Agent of the Week, highlighting the growing importance of security integrations.
This Week in Numbers
- Total Agents & Tools Indexed: 257,686
- New Agents & Tools Added: 9,441
- Models & Datasets Indexed: 2,948,923
- Total AI Assets Indexed: 4,151,195
Agent of the Week
Name: Panther Labs
Source: PulseMCP
Trust Score: 75.2
Stars: 42
Description: Integrates with Panther Labs' cybersecurity platform to enable security alert triage, data lake querying, detection rule management, and log source analysis for incident response and threat hunting workflows.
Framework Trends
The top frameworks remain consistent, but there is a notable increase in the "community" category. Anthropic and OpenAI continue to dominate with 7,512 and 6,333 entries respectively. The community framework count has risen by 955 new additions this week.
MCP Server Growth
This week saw an addition of 553 new MCP servers, bringing the total to 4,151,195. Key new additions include:
- BrowserStack: Integrates with testing infrastructure for cross-browser and mobile app verification.
- Panther Labs: Enhances cybersecurity platform integration for alert triage and threat hunting.
- Mobile Device Control: Enables remote control of Android and iOS devices for automated testing.
Trust & Compliance
The trust score distribution shows a balanced mix:
- High: 5,127
- Medium: 183,852
- Low: 68,707
The average trust score is 49.9, indicating a generally high level of confidence in the indexed assets.
Outlook
The ongoing growth in community-based frameworks and cybersecurity tools suggests an increasing focus on collaborative development and enhanced security measures within the AI ecosystem.
Originally published on nerq.ai
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