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    MCP-native agent evaluation and observability server. Log traces, evaluate output quality with 12 built-in rules (PII detection, prompt injection, cost thresholds), and track agent costs. Real-time dashboard, OTel-compatible spans. Self-hosted, MIT licensed.
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    MIT
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    8 standalone MCP servers for SMBs — Guardrails (prompt injection, PII, secrets detection), FinOps (AI cost tracking and budgets), Observability (agent tracing), Smart Router (17+ models, 9 providers), Trust Score (governance scoring 0-100), Memory (persistent agent memory), ThinkSecure (runtime security + SOC2/GDPR audit), and A2A Lite (agent-to-agent protocol). 37 tools total, TNC credits
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    MIT
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    Provides read-only access to Jaeger distributed tracing data through the Model Context Protocol. Enables Claude and other MCP-capable agents to search traces, inspect spans, and analyze service dependencies directly within conversations.
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    MIT
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    An MCP server that gives coding agents programmatic access to Sumo Logic logs via the Search Job API, enabling issue triage in preview deployments and production without leaving the editor.
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    Apache 2.0
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    A read-only MCP server that enables AI assistants to search, aggregate, and explore OpenSearch log data through 12 tools for connectivity, index discovery, search, and aggregations.
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    MIT
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    Enables AI assistants to access full Datadog observability, including log search, APM trace filtering, smart sampling, and cross-correlation between logs, traces, and metrics.
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    Apache 2.0
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    A read-only MCP server for querying Sumo Logic logs, enabling AI assistants to search and investigate application logs with opinionated tools and secure credential handling.
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    MIT
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    Enables querying Graylog log management system for messages using natural language, supporting multiple instances and flexible search parameters.
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    MIT
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    Enables AI-powered analytics for OpenReplay user sessions through natural language queries. Supports session search, user journey analysis, error tracking, performance metrics, and funnel analysis to understand user behavior patterns.
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    Enables interaction with Datadog's monitoring platform to search logs, search trace spans, and perform trace span aggregation for analysis.
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    MIT
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    Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.
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    Apache 2.0
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    A Model Context Protocol server that provides AI agents with controlled read access to Datalust Seq instances for log analysis and monitoring. It enables agents to search events, execute data queries, and retrieve information about signals, dashboards, and alerts.
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    MIT
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    Model Context Protocol server for managing and diagnosing GlassFlow streaming pipelines, exposing pipeline CRUD, metrics queries, log search, and a composite diagnostic tool as MCP tools that AI agents can call over SSE transport.
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    Apache 2.0
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    A comprehensive, AI-powered performance analysis and monitoring platform for OpenShift/Kubernetes clusters. This project provides Model Context Protocol (MCP) servers for analyzing etcd, network, and OVN-Kubernetes components with deep performance insights, automated root cause analysis, and actionable recommendations.
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    Apache 2.0
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    Connects AI coding assistants to Shipbook for investigating issues using real application logs with error classification, log search, and session tracing.
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    MIT