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Multi-source AI news clustered, deduplicated, and scored 0–100 across authority, cluster strength, headline signal, and time decay.

  1. TOOL · dev.to — MCP tag English(EN) ·

    We Scored 14,824 MCP Servers on Behavioral Trust — Here's What We Found

    Dominion Observatory, a new tool developed by Dinesh, has analyzed 14,824 Multi-Agent Conversation Protocol (MCP) servers to assess their behavioral trust. The average trust score across these servers is 64.5 out of 100, indicating a general lack of reliability for AI agents selecting tools dynamically. High-trust servers are characterized by consistent response times, high success rates, and active maintenance, with Dominion Observatory offering a directory and framework integrations to help agent builders filter for dependable MCP servers. AI

    IMPACT Provides a crucial trust metric for AI agents selecting external tools, potentially improving reliability and safety.

  2. RESEARCH · dev.to — MCP tag English(EN) · · [2 sources]

    Manifold Security Just Scored 7,700 MCP Servers. Here's Why That Number Should Worry You.

    Two security firms, Manifold Security and Dominion Observatory, have developed systems to score the trustworthiness of Model Context Protocol (MCP) servers, which are increasingly used to connect AI agents to external tools. Manifold Security's Manifest platform analyzes over 7,700 MCP servers by evaluating publisher provenance and the server's declared interface for manipulative instructions. Dominion Observatory, on the other hand, scores over 14,800 MCP servers based on their runtime behavior, including success rates, latency, and uptime, to detect degradation or compromise that static code analysis might miss. AI

    Manifold Security Just Scored 7,700 MCP Servers. Here's Why That Number Should Worry You.

    IMPACT Addresses critical security and reliability concerns for AI agents connecting to external tools, potentially impacting enterprise adoption and agent safety.