"Integrating Web3 Wallet Functionality in AI Chat Applications" matching MCP servers:

Self-hosted AI orchestrator that monitors and manages homelab services, exposing them as MCP tools for LLMs to drive.

Enables AI assistants to query system health, metrics, service reconnaissance, run multi-node patrols, and send incident alerts across distributed infrastructure through MCP tools.

Universal database copilot for diagnostics, operations, and performance analysis via MCP and CLI.

MCP server that exposes AI credit usage data from OpenMeter to the TAIS AI chat service, automatically scoped to the calling tenant and restricted to admin users.

MCP server that diagnoses Apache Spark job failures and optimizes performance using stack-trace analysis and LLM providers, supporting EMR and local sources.

Enables querying Margint per-customer AI margins and costs from MCP clients. Provides tools to list customers, drill into costs, check budgets, and view workspace-wide cost breakdowns.

A read-only MCP server that exposes AI Disk Doctor Core's scan, model inventory, and history tools via local stdio, with no mutation or shell capabilities.

Enables AI agents to manage prompts and sessions via the ai-agent-logs API, with tools for health checks, login, listing/creating prompts, and retrieving sessions.

Track brand visibility across ChatGPT, Perplexity, Claude, and Gemini.

Provides AI-aware failover for Mihomo proxy on macOS by validating real OpenAI paths and switching proxy groups after verified hard failures. It offers a local stdio MCP server for diagnostics, status, and safe management of the AI proxy group.

Enables LLMs to query telemetry data via the Spyglass AI agent, providing intelligent insights about application performance, errors, and bottlenecks.

A MCP server for tracking AI usage metrics and structured logs across applications. Monitor model calls, analyze usage patterns, track costs, and debug AI interactions.

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.

Enables running Jira project health audits directly in Claude Desktop, providing real-time health scores, risk detection, and team workload analysis through natural language.

Enables MCP-compatible clients to search approved local Markdown runbooks, retrieve selected local host health details, and get bounded Kubernetes pod-status summaries for allowlisted clusters and namespaces.

Connects AI assistants to the Vectra AI security platform to enable intelligent analysis of threat detection data and automated incident response workflows. It allows users to investigate threats, take response actions, and generate security reports using natural language.

Enables AI assistants to monitor and analyze industrial process data from DCS/SCADA systems via MCP protocol, with domain expert knowledge for anomaly detection and recommendations.

Exposes read-only tools for OPC UA PLC tag monitoring and diagnostics, and enables template-driven, validated IEC 61131-3 SCL code generation with a mandatory human review gate before download.

Transforms Elasticsearch into an AI-powered observability engine for analyzing logs, APM traces, and system metrics through natural language.

AI Ops - MCP server providing AI-powered tools and automation by MEOK AI Labs

Health Check AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Enables AI assistants to see which model IDs each provider's API has started listing since the last check, and to list the models a given provider currently serves with optional substring filtering, all without spending tokens.

Enables read-only, workspace-bound inspection of repositories and log files, returning JSON reports with file counts, largest files, TODO/FIXME markers, and warning/error counts.

Enables AI agents to analyze, cluster, compare, and export reports from local log files through seven read-only tools, returning compact evidence packs with line-number citations instead of raw log dumps. All processing happens on the local machine, so log data never leaves the environment.

Edge-deployed predictive decision engine and circuit-breaker orchestrator for AI agents. Features low-latency telemetry, automated failover routing, and Bitcoin Lightning micro-payments.

Multi-model AI visibility audit: asks ChatGPT, Perplexity and Grok what they know about a brand, then scores GEO/SEO health with benchmark percentile.

Enables AI agents to analyze text and retrieve real-time system metrics such as CPU, memory, and uptime through LangChain tool calling, with an embedded web UI for testing queries and viewing tool execution logs.

Enables natural language queries for device support, including resolving device references, retrieving device details, historical metrics, and checking provisioning status. Maintains conversation context for multi-turn interactions.

Enables external AI clients to autonomously execute backend tools via SSE, including system health checks, within a FastAPI async microservice with conversational memory.

Compresses log files into templates and statistics using Drain3, and exposes them to AI assistants via an MCP server for efficient log monitoring and anomaly detection.