"Personalized Summary Service" matching MCP servers:

Authenticated email service MCP for AI agents.

AI-powered coaching for runners, cyclists, swimmers, and triathletes, enabling personalized workouts, training plan adaptation, performance analytics, and AI coaching via Claude, MCP clients, or HTTP.

Compare service-grant changes, tool alias origins, and saved MCP tool definitions with Gooo rules. Reports preserve incomplete-capture uncertainty and source bindings. No grants are applied and no compared tools are invoked.

Local ledger for development ports: leases a block of ports per project slot (one per working copy), renders env files, and resolves service names to URLs. No daemon, no listener.

Enables AI agents to ask what changed in a time window and get back a short, ranked answer across metrics, logs and traces, with the service where a failure started identified and its echoes in other services labelled as such. Read-only and deterministic, it scores changes against a baseline and trims results to a token budget, so agents avoid paging through raw queries and blaming the loudest symptom.

Connects coding agents to local development services managed by Kranz. Agents can inspect service health, ports, logs, and run history, and perform lifecycle actions through the same live runtime as the TUI and CLI.

Enables AI assistants to manage and query Tiger Cloud database services, including service lifecycle operations, database connections, and SQL execution.

deptrust is a CLI that checks package versions for known vulnerabilities across npm, PyPI, crates.io, Go modules, RubyGems, NuGet, Maven, Packagist, pub.dev, CocoaPods, Hex.pm, Hackage, GitHub Actions, and more. It runs locally as a CLI and as an MCP server. It calls public package registry and OSV APIs directly; there is no hosted deptrust service to trust or configure.

Talk to AWS CLI from an MCP-speaking agent. Run any aws <service> <operation> command through the Model Context Protocol, with read-only defaults and gated write access.

Self-hosted OpenTelemetry backend in one Go binary. Its MCP server exposes tools for service health, latency, topology, trace inspection, log search, read-only SQL over traces, logs and metrics, and dashboards.

Enables coding agents to navigate and score brownfield multi-service flows by mapping use-case trees, tracing loadouts and consumers, and detecting drift.

A command-line interface and MCP server for managing and monitoring multiple development services through a unified terminal UI. It enables users to interact with service logs, filter messages, and control development environments directly via Model Context Protocol integration.

Enables AI agents to review and compare Go goroutine dumps, surfacing goroutine leaks, lock pile-ups, exhausted database pools, and missing HTTP timeouts from dump text alone without connecting to the service.

Enables AI assistants to interact with MAAS (Metal as a Service) infrastructure for machine management, network configuration, and storage management through a standardized JSON-RPC 2.0 interface.

Provides a single local MCP endpoint that connects Gmail, GitHub, Slack, Notion, and Linear once, with multiple accounts per service, so any AI agent can use per-agent tokens, policies, and optional result filtering without re-authenticating.

Enables AI assistants and automation agents to query Talos Linux clusters and nodes for versions, events, service and kernel logs, resource usage, and discovery members through the Talos API, with read-only tools by default and optional node reboot when explicitly allowed.

Provides comprehensive access to the New Relic observability platform through 55 MCP tools, enabling APM, infrastructure, logs, traces, alerts, dashboards, synthetics, workflows, notifications, service levels, tags, entities, and workloads via a single GraphQL endpoint.

A gateway service that connects AI assistants to numerous external tools like Notion, GitHub, and Google Workspace through a single Model Context Protocol endpoint. It provides a centralized hub for managing multiple tool integrations with secure authentication and a unified API architecture.

Enables AI assistants to explore and understand Protocol Buffer (.proto) files through fuzzy search, service definitions, and message structure analysis. Integrates with Cursor IDE to provide natural language queries about protobuf schemas and API definitions.