"A library or package named 'pubmedmcp@0.1.3'" matching MCP connectors:
Matching Connector Tools:
Read monitors, incidents, heartbeats, on-call and status pages; acknowledge or resolve incidents.
Run a prompt through a LangChain (system + human) chain over Gemini on Vertex AI; optional LangSmith
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.
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.
Uptime, SSL, DNS and domain monitoring you can talk to from Claude or any MCP client.
Mobile observability for AI agents. Investigate crashes, hangs, ANRs, bugs, and app performance, and triage app store reviews, directly from your IDE or terminal.
Enable secure connectivity between Sentry issues and debugging data, and LLM clients, using a Model Context Protocol (MCP) server.
Read-only MCP access to a documented IT fleet: state, changes, posture. 15 tools.
MCP-native AI SRE: ask what's broken in production, get a reviewed GitHub fix PR.
Log, evaluate, and ground AI decisions against authority context. Returns PASS, WARN, or BLOCK.
MCP-native AI SRE. Exposes your production OpenTelemetry problems, traces, and logs over the Model Context Protocol, plus an AI remediation loop that opens a reviewed GitHub fix PR and verifies in production (reopening on regression). Tools include list_problems, get_problem, query_traces, detect_anomalies, and request_problem_remediation. Human-in-the-loop by default — the merge button stays yours.
Interact with a global network measurement platform.Run network commands from any point in the world
A paid remote MCP for Decapod, built to return verdicts, receipts, usage logs, and audit-ready JSON.
A paid remote MCP for Skybridge, built to return verdicts, receipts, usage logs, and audit-ready JSO
A paid remote MCP for AI SDK MCP gateway registry, built to return verdicts, receipts, usage logs, a
A paid remote MCP for AI SDK data query MCP, built to return verdicts, receipts, usage logs, and aud
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.