"How to add a note to an order or object" matching MCP servers:

MCP server enabling AI agents to trace and resolve order synchronization incidents between an ERP (Odoo) and multiple marketplaces.

Enables AI agents to debug and repair historical Solaris/SPARC systems by providing an out-of-band control plane with guest DTrace, QEMU monitor access, SPARC-aware GDB, host eBPF/perf tracing, and an immutable evidence ledger for cross-layer hypothesis testing.

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

An MCP server that provides cost and reliability observability for LLM and agent workflows. It records model calls and allows querying and aggregating telemetry data through MCP tools.

Enables AI agents to monitor Docker containers, system resources, ports, and logs in real-time.

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.

Privacy friendly, cookieless web analytics built MCP-first. "Add analytics to my Next.js app" → an AI agent runs the setup_analytics_for_site tool, picks the right install snippet, edits your layout file, and verifies the script is loading. OAuth onboarding, no API keys to paste.

Ask your AI agent about your MCP servers: which tools fail, how a release compares, what clients look for and do not find. Reads from mcpspan with a read token.

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.

Maintenant modern monitoring for docker and kubernetes. NOTE : Is local server, you can't see online deployments

An MCP server that enables coding agents to log their work, decisions, test runs, PRs, and progress as structured events, either to a local JSONL file or an HTTP endpoint.

Сonnects to live JVMs via JDWP protocol, enabling LLM agents to autonomously debug Java applications — attach to a running process, pause threads, set breakpoints (including conditional), inspect stacks with auto-resolved object fields, evaluate methods, set variable values, and diagnose issues like deadlocks and hung queries.

Read-only MCP server for TrueNAS Scale debugging, providing k3s tools for kubectl operations and whitelisted midclt calls for system info, apps, and pools.

An MCP server implementation that enables dynamic configuration of OpenTelemetry Collectors, allowing users to add, remove, and configure receivers, processors, and exporters through MCP tools.

Enables grading a website's security headers with per-gap fixes and a README badge, and analyzing logs, code, configs or suspicious messages to determine what happened, how severe it is, and what to fix first. Requests are masked for sensitive data and automatically retried across multiple AI providers when one refuses, subject to a defensive-use-only policy.

Gives AI agents read-only access to production NATS and JetStream event buses through twenty-five bounded, schema-typed tools covering message search, dead-letter inspection, causal flow reconstruction from a request or correlation id, and stream, consumer, KV, object-store and server-health topology. Because the runtime is wired only to read paths and every result is limited, cursored and truncation-flagged, agents can debug live traffic without any ability to mutate it.

Enables a human supervisor’s MCP client to inspect policies, agents, trust scores, and runs, and to pause, resume, kill, approve, reject, edit run memory, or override an agent’s next tool call.

An MCP-native enterprise operations platform that unifies team management, product catalog, order processing, knowledge base, location intelligence, analytics, and DevOps monitoring into a single server accessible from any MCP-compatible AI agent.

A zero-infrastructure, local proxy that wraps any stdio MCP server to add audit logging, policy enforcement with regex guards, and per-session/per-day budgets.

Enables simulation of production incident alerts and resolution by exposing an active alerts resource and a tool to restart services with simulated success or failure outcomes.