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JetBrains incubator Kotlin and JVM agent framework for building predictable, fault-tolerant AI agents with graph workflows, tools, MCP integration, memory, streaming, OpenTelemetry, Spring/Ktor integrations, and multiple LLM providers.

Analyze distributed traces and LLM observability data from Claude — search traces and spans, find errors, list services, analyze LLM token usage, identify slow LLM operations, and discover AI model usage patterns — with the OpenTelemetry MCP server supporting Jaeger, Grafana Tempo, and Traceloop backends.

Expert capability pack for Agent SDK OpenTelemetry export using CLAUDE_CODE_ENABLE_TELEMETRY, OTLP exporters, and monitoring-usage reference variables documented for Claude Code CLI subprocesses.

Community reusable agent prompt for analyzing OpenTelemetry traces from agent hosts using official trace signal documentation: span hierarchy review, latency attribution, error propagation, and privacy-safe instrumentation recommendations.

Apache-2.0 agentic proxy that can expose stdio, HTTP, SSE, and Streamable HTTP MCP servers through a managed gateway with federation, OAuth/JWT authentication, RBAC/CEL policy, CORS, TLS, observability, and Kubernetes Gateway API support.

A practical walkthrough of exporting OpenTelemetry traces, metrics, and events from the Claude Agent SDK: enabling telemetry, configuring OTLP exporters, reading agent spans, linking traces to your app, and controlling sensitive data.

Official Datadog MCP Server for connecting Claude, Codex, Cursor, and other MCP clients to Datadog observability, incidents, logs, metrics, traces, dashboards, monitors, notebooks, services, and security signals.

Instrument AI agent systems with high-signal telemetry and runbook-driven incident response for reliability and safety.

Query observability data, manage dashboards, and monitor your systems from Claude — run APL queries against datasets, list metrics, inspect monitors, and retrieve saved queries — with the official Axiom remote MCP server.

MIT-licensed OpenClaw skill and plugin registry with a hosted catalog, `clawhub` CLI, npm package, native OpenClaw install flows, SKILL.md publishing, plugin package publishing, vector search, scan status, moderation controls, install lockfiles, and opt-out install telemetry.

Source-backed rules for AI workflow directories that need consistent privacy metadata before accepting entries that touch prompts, files, local tools, hosted services, telemetry, generated artifacts, or personal data.

A source-backed Model Context Protocol starter collection for SaaS builders: connect product code, database state, payments, deployment telemetry, issue tracking, and production errors while keeping MCP authorization and tool boundaries explicit.

The Claude Code data-handling controls that matter for teams working near PHI: no-training commercial policy, retention windows, Zero Data Retention, encryption, local transcript handling, telemetry opt-outs, and security model.

Open-source observability platform purpose-built for AI agents, with OpenTelemetry-native tracing, plain-English signals, an evals SDK and CLI, SQL dashboards, dataset annotation, and MCP/CLI access, self-hostable with Apache-2.0 SDKs for Python and TypeScript.

Microsoft framework for building, orchestrating, and deploying production AI agents and multi-agent workflows across Python and .NET, with workflows, middleware, OpenTelemetry, Foundry hosting, A2A, MCP, and Semantic Kernel migration support.

Expert Claude Code analytics adoption capability pack for enabling team and enterprise dashboards, GitHub contribution metrics, adoption tracking, ROI reporting, and OpenTelemetry complements with source-backed rollout steps.

Query OpenTelemetry traces and metrics, manage dashboards, analyze distributed traces, and investigate exceptions from Claude — with the official Pydantic Logfire remote MCP server hosted at logfire-us.pydantic.dev/mcp.

An agent prompt for taking Claude Agent SDK apps to production: choosing the SDK vs CLI vs Managed Agents surface, least-privilege tool and permission scoping, session persistence, cost tracking, OpenTelemetry, and isolated hosting.

A practical guide to instrumenting LLM and agent applications with traces, metrics, logs, GenAI semantic attributes, sampling, and privacy-aware redaction so teams can debug model calls, tool use, retries, and cost.