"How to use Bootstrap framework" matching MCP servers:

Lets you use Claude Desktop, or any MCP Client, to use natural language to accomplish things on your Cloudflare account.

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.

A framework for building MCP servers with built-in enterprise capabilities such as authentication, authorization, telemetry, audit logging, and data classification, allowing domain developers to focus on business logic while maintaining governance and compliance.

A minimal guardrails framework for AI agents, acting as an MCP proxy to enforce policies, approvals, and audit logging on tool calls.

Analyzes how search engines and AI systems discover, crawl, cite, and convert traffic via CLI and MCP tools.

Enables monitoring and analysis of agent goal achievement and failures across sessions, repos, and tools, with detailed views and tracing.

Radar is an open-source Kubernetes observability and diagnostics MCP server. It exposes cluster health, workload diagnosis, logs, events, topology, audit findings, and remediation actions to AI agents through the Model Context Protocol.

Enables AI assistants to search, analyze, and debug application API traffic captured by Tusk Drift, including HTTP requests, database queries, distributed traces, latency metrics, and error rates.

Fetches Langfuse observability traces directly into a VS Code coding agent's context, enabling querying and viewing trace data through natural language.

Provides read-only access to OpenFolio data, enabling catalog, holdings, grid, and log queries without placing orders.

Read-only MCP server that exposes Grafana dashboards, datasources, and metric/log queries as tools, for use by skills in the TICKETS workspace.

MCP server for Drumbeats monitoring. Enables creating monitors, triaging incidents, and running HTTP/SSL/DNS checks using natural language from any AI client.

An MCP server exposing 72 tools across 26 homelab services, enabling LLMs to monitor and manage infrastructure, media, storage, and networking with a single endpoint.

eBPF-based GPU causal observability agent with MCP server. Traces CUDA Runtime and Driver APIs via kernel uprobes and host events via tracepoints to build causal chains explaining GPU latency. 7 tools: get_check, get_trace_stats, get_causal_chains, get_stacks, run_demo, get_test_report, run_sql. Telegraphic compression reduces token usage ~60%. Supports stdio and HTTPS (TLS 1.3) transport.

Governed, read-only OT data tap for substation and utility telecontrol — IEC 60870-5-104, DNP3/IEEE 1815, and IEC 61850 MMS connectors with cross-protocol asset discovery, alarm and downtime RCA, unbypassable audit logging (MCP + CLI), budget/runaway guards, and an airgap no-egress mode. Energy edition of Industrial-AIOps, built on iaiops.core.

Zero-config MCP server that gives AI coding assistants a real-time diagnostic snapshot of your local dev environment. Detects framework, running services, recent errors, git state, and provides a health diagnosis in one call.

Estimates the environmental footprint of your AI use — energy (kWh), miles driven, water used for cooling, and CO₂ — plus a prompt-efficiency score, working with any AI client by measuring token usage.

A Model Context Protocol server that enables AI assistants to interact with Sentry for error tracking and monitoring, allowing retrieval and analysis of error data, project management, and performance monitoring through the Sentry API.

Enables MCP clients to interact with a local AI agent through Ollama, providing tools for checking weather, current time, and available models, while tracing calls to Langfuse.

A specialized diagnostic framework that enables AI models to self-diagnose and fix MCP-related issues by analyzing logs, validating configurations, testing connections, and implementing solutions.