"Improving the Intelligence of Large Language Models" matching MCP servers:

MCP server for semantic log ingestion, hybrid retrieval, and cleanup, enabling natural-language querying of log files with dense+BM25 retrieval and full provenance.

Analyzes AI agent traces to diagnose failures, score performance, and provide actionable fixes using tools like judge_trace and trace_breakdown.

Enables AI agents to investigate Splunk exports or live queries using deterministic detectors and an iterative analysis loop, all running locally without data leaving the machine.

Aggregates real-time threat intelligence from multiple sources including Feodo Tracker, URLhaus, CISA KEV, and ThreatFox, with IP/hash reputation checking via VirusTotal, AbuseIPDB, and Shodan for comprehensive security monitoring.

Extends Veeam Intelligence to MCP-compatible clients, enabling secure, real-time operational insight across Veeam Backup & Replication, Veeam ONE, and VSPC via natural language or AI workflows.

MITM proxy MCP server that intercepts and verifies AI agent tool calls, detecting fabrication, tracking costs, verifying outcomes, and inferring user satisfaction.

A verifying MCP gateway that pins approved tool manifests and skill files to content addresses, blocking tampered descriptions before they reach model context.

Provides MCP tools to create and query SigNoz trace funnels, enabling agents to measure their own step conversion rates from within the agent loop.

Enterprise AI operator evaluation MCP server. 27 tools (22 read + 5 write) for measuring, benchmarking, diagnosing, and interv ening on how human operators use AI tools across 5 canonical metrics.

Enables natural language interaction with Plausible Analytics data to query traffic, visitors, engagement, and more using conversational questions.

Read-only MCP server that surfaces UniFi network data from a UCG-Fiber console to Claude, enabling monitoring of hosts, sites, devices, clients, ISP metrics, and device stats via read-only API tools.

Enables AI assistants to query software supply chain compliance data, including asset status, security vulnerabilities, and evidence lineage. It allows for natural language analysis of compliance posture, policy violations, and deployment blockers across an organization.

MCP server for log file analysis. Gives LLMs the ability to efficiently analyze large log files without loading them into context.

MCP server for measuring, tracking, scoring, and improving AI agent reliability with tools for recording interactions, scoring reliability, analyzing failures, recommending improvements, generating audit reports, and checking MCP health.

A Model Context Protocol (MCP) server for the Pingera monitoring service, providing seamless integration between AI models and monitoring data.

Enables autonomous context window management, prompt caching, token optimization, and real-time observability for AI coding agents across multiple IDEs, reducing token costs and improving performance.

A production-ready Model Context Protocol (MCP) server for seamless integration between Wazuh SIEM and Large Language Models (LLMs).

Reliability intelligence for remote MCP servers. Agent-native discovery for 1,700+ servers with uptime monitoring and latency benchmarks.

A TypeScript implementation of a Model Context Protocol server that connects to Sentry error tracking service, allowing AI models to query and analyze error reports and events.

An MCP server that records agent execution metrics and exposes a Context Window Explorer to visualize exactly what entered the model's context window across sessions, tokens, and tool calls.