"How to operate notes in the Memos app" matching MCP servers:

MCP server for IBM Concert Operate that exposes the full v2 REST API as callable tools, enabling AI assistants to manage alerts, incidents, policies, runbooks, and more.

A small notes server exposing scoped, cacheable tools over streamable HTTP, with OAuth token introspection and resource-server metadata so callers are identified per user. It enforces per-subject rate limits as tool-level errors and emits OpenTelemetry spans following MCP semantic conventions, and can also run locally over stdio without auth.

Enables tracing every tool call from a ChatGPT app into LangSmith, one run per tool call, grouped per conversation thread. Provides thread-level evaluation and monitoring of tool interactions.

A verifying MCP gateway that pins approved tool manifests and skill files to content addresses, blocking tampered descriptions before they reach model context.

Fetches Langfuse observability traces directly into a VS Code coding agent's context, enabling querying and viewing trace data through natural language.

Lets an assistant read recorded production AI agent runs — steps, model and tool calls with arguments, and outcomes — along with the findings of comparison runs that checked a prompt or model change against those recordings, and verify a signed evidence bundle offline with no account or network. It is strictly read-only: no tool starts a replay or comparison, so nothing can spend money or act without a person deciding.

Enables natural language interaction with Plausible Analytics data to query traffic, visitors, engagement, and more using conversational questions.

Enables AI assistants to query and analyze AI agent sessions from observability providers like Shepherd (AIOBS) and Langfuse, allowing users to debug agent runs, compare sessions, track performance, and analyze LLM usage patterns.

MCP server for Uptrack uptime monitoring. Manage monitors and incidents from AI agents like Claude, ChatGPT, and Cursor.

Enables an AI assistant such as Claude to read and edit the self-hosted network inventory: search and manage entries, check live TCP reachability, map hosts, link and derive relationships, inspect topology, compare configured read-only sources like Docker, OPNsense, AdGuard and Traefik against what is declared, surface conflicts and new devices, and review the audit log.

A lean MCP server that provides LLM agents with transparent access to multiple Prometheus instances for metrics analysis and SRE operations.

Read-only MCP server that surfaces UniFi network data from a UCG-Fiber console to Claude, enabling monitoring of hosts, sites, devices, clients, ISP metrics, and device stats via read-only API tools.

A Model Context Protocol (MCP) server that lets an AI assistant read and operate the Lumics network monitoring platform via its REST API.

Lets AI agents query, manage, and operate their LLM observability data directly from the conversation. Provides 87 tools for cost analysis, alerting, anomaly detection, and runtime control gates.

The logs of everything on one machine — app, build, GPU, containers, serial board, OS — interleaved in the order they happened, and readable by an agent. Read-only: it can tail, search and wait, and it cannot write, delete or configure anything.

Enables any MCP-compatible agent to query, diagnose, map, and operate Elasticsearch or OpenSearch clusters via REST, with read-only defaults and layered safety controls.

Enables AI agents to inspect a live Celery deployment over RabbitMQ or Redis — checking which workers are responding, their pools, concurrency and consumed queues, and how many messages are backed up in each queue — so agents can diagnose stuck or unrouted tasks. Read-only by default, with broker credentials masked in all output.

Enables AI agents to inspect and operate multiple Kubernetes clusters through natural language, providing multi-cluster diagnostics, RBAC analysis, security checks, and app-centric deployment with GitOps and smart workload placement.

Enables AI clients like Claude to triage, investigate, and operate Icinga installations through natural language, integrating with Icinga's REST APIs and providing deep awareness of monitoring plugins and historical performance data.

Enables AI clients to safely query and operate SQL databases with per-statement risk grading, two-phase confirmation for dangerous operations, and access-level enforcement. Every action is recorded in a tamper-evident hash-chain audit log with integrity verification.

Windows tray process that exposes local ambient context (presence, foreground app, battery, etc.) as MCP tools with privacy classification and opt-in controls.

Let AI agents observe and operate your Hatchet workflows: runs, logs, workers, metrics, plus trigger/cancel/replay.

Enables AI assistants to operate and monitor Windows workspaces through native tools for filesystem operations, PowerShell execution, background tasks, Windows services, GPU telemetry, PDF generation, and a built-in web gateway/dashboard.

Enables AI agents to safely and audibly operate PostgreSQL databases and their Docker environments, offering schema inspection, guarded queries, migrations, performance diagnosis, and container management tools.

A lightweight MCP server that enables AI assistants to deploy, inspect, and operate Kubernetes workloads through high-level workflow tools, reducing token usage with structured outputs.

Analyzes how search engines and AI systems discover, crawl, cite, and convert traffic via CLI and MCP tools.

Embeds a runtime MCP inspector in a NestJS app so coding agents can inspect the module and provider graph, routes and their guards/interceptors/pipes/filters, logs, request traces, event listeners, and scheduled jobs through an HTTP endpoint.

Enables external CLI agents to directly operate TauriTavern via MCP, including reading runtime data, executing STScript, sending messages, switching characters, and running JavaScript diagnostics in iframes.

An MCP server that records agent execution metrics and exposes a Context Window Explorer to visualize exactly what entered the model's context window across sessions, tokens, and tool calls.

Provides cryptographically signed, tamper-evident compute usage receipts via a Model Context Protocol server, exposing tools to record usage, verify receipts, list the ledger, and verify ledger integrity without requiring any account, API key, or single cloud provider.