"Email organization system using LLMs with IMAP integration" matching MCP connectors:
Matching Connector Tools:
Public MCP digital twin with synthetic systems and an agent firewall. No customer data.
Run a prompt through a LangChain (system + human) chain over Gemini on Vertex AI; optional LangSmith
AI-ready vendor incident status with public active incidents and plan-scoped history.
Connect engineering metrics, DORA performance, and deploy risk scoring to any AI assistant. Score PRs for deployment risk using a 36-signal model, query team health, incidents, coverage, and more.
The Google GKE MCP server is a managed Model Context Protocol server that provides AI applications with tools to manage Google Kubernetes Engine (GKE) clusters and Kubernetes resources. It exposes a structured, discoverable interface that allows AI agents to interact with GKE and Kubernetes APIs, enabling them to inspect cluster configurations, retrieve Kubernetes resource YAMLs, monitor operations like cluster upgrades, diagnose issues, and optimize costs—all without needing to parse text output or use complex kubectl commands.
High-performance array aggregation and metrics clearing engine. Cleans and bucket-groups noisy metric streams via an $O(N)$ single-pass data sweep. Operates natively with the pay-per-call x402 micropayment framework.
Real-time infrastructure monitoring with metrics, logs, alerts, and ML-based anomaly detection.
Monitor, troubleshoot, and optimize your technology stack with Intelligent Observability.
Connect AI assistants to AppAmbit — the command center for your mobile & desktop apps. Query real-time analytics, sessions, and crash reports; read and push remote config; send push notifications, provision and query managed per-app SQLite databases, deploy serverless Cloud Code functions; and manage a headless CMS. Also generates SDK setup snippets and runs integration diagnostics. Supports .NET MAUI, Swift, Objective-C, Android and more. Built for indie devs, mobile teams, and agencies.
Enable secure connectivity between Sentry issues and debugging data, and LLM clients, using a Model Context Protocol (MCP) server.
Interact with a global network measurement platform.Run network commands from any point in the world
Paid remote MCP for agent design system guard MCP, structured receipts, audit logs, and reviewer-rea
AI agent run monitoring with incident replay and SLA receipts.
System self-awareness, health monitoring, and autonomous self-repair
Debug production issues using Shipbook logs and Loglytics error insights.
Uptime monitoring with 127 tools across 23 protocols. Tag filtering + Code Mode.
The Polar Signals MCP server enables AI assistants to connect directly with performance profiling data, allowing users to analyze application performance through natural language queries. Key capabilities include querying CPU performance and memory usage, exploring profiling metadata like profile types and labels, and providing AI-driven code optimization suggestions directly within development environments like Claude Code or Cursor.
The Buildkite MCP server exposes Buildkite product data (pipelines, builds, jobs, and test data) to AI tools, editors, and agents through the Model Context Protocol. It provides capabilities including pipeline creation and management, build monitoring with specialized tools like 'wait_for_build', efficient log querying using Apache Parquet conversion and caching, and OAuth-based authentication for both read-write and read-only access to Buildkite's REST API.