"Collaboration Between Multiple AIs via MCP (Master Control Program)" matching MCP servers:

A local-first MCP server that gives AI coding agents runtime visibility and AI-managed debug logging. It replaces blind print() debugging by turning runtime execution into causal chains, allowing agents to instantly locate bugs by finding missing .success events in Python and TypeScript code. Single binary with MCP, CLI, and HTTP interfaces.

MCP server for the Production Master incident-investigation service, enabling any MCP client to drive investigations via tool calls with pass-through authentication.

Enables triggering, streaming, and reviewing autonomous production-incident investigations directly from your editor, with human-gated approval for any mutating actions.

Provides read-only access to query and retrieve information about devices, fleets, events, and configurations managed by Flight Control through a safe integration layer supporting filtering and selector-based queries.

The policy enforcement plane for MCP: deterministic admission and egress policy, attributable audit, and SIEM export for your MCP server fleet. Self-hosted and MIT licensed.

Minimal MCP server that integrates with Graylog, enabling agents to search, analyze, and inspect log messages across streams, discover fields and streams, and query multiple Graylog instances.

MCP server for Blue Iris NVR, enabling camera health checks, live/historical snapshots, clip/alert search, and PTZ control via the Blue Iris JSON API.

Enables querying logs, traces, and metrics from multiple OpenObserve instances via MCP tools, with parallel execution, batching, and caching.

An MCP server that gives AI agents full visibility and control over your Dagster instance, enabling autonomous monitoring, diagnosis, and remediation of data pipelines.

Enables AI assistants to search logs, query metrics, manage dashboards, analyze APM traces, and control monitors via Datadog APIs.

Enables running Lighthouse web performance audits via MCP, providing Core Web Vitals, performance scores, and optimization suggestions for single or multiple URLs.

MCP server for Portkey Admin API - 116 tools for prompts, configs, analytics & more.

An MCP server that enables AI agents to safely operate multi-cluster Kubernetes fleets through an Open Cluster Management hub, with policy enforcement, human approval, and audit tracing.

Enables AI assistants to access full Datadog observability, including log search, APM trace filtering, smart sampling, and cross-correlation between logs, traces, and metrics.

Finds problems in your MCP servers before your users do. Scans your Claude config, checks every server's capabilities, actually calls tools to make sure they work, and catches breaking changes between versions.

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.

Provides seamless integration between AI assistants and Prometheus, enabling natural language interactions with your monitoring infrastructure. This server allows for effortless querying, discovery, and analysis of metrics.

Enables MCP clients to explore ClickHouse schemas, run analytical queries, and manage the database with statement-aware security modes and access-control flags.

Enables querying Graylog log management system for messages using natural language, supporting multiple instances and flexible search parameters.

Aggregates status of multiple SaaS providers into a single MCP server, enabling AI agents to check service health and incidents via tools like list_services, get_status, and check_all.