"An overview of semiotics and its concepts" matching MCP servers:

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.

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

MITM proxy MCP server that intercepts and verifies AI agent tool calls, detecting fabrication, tracking costs, verifying outcomes, and inferring user satisfaction.

Provides MCP tools to create and query SigNoz trace funnels, enabling agents to measure their own step conversion rates from within the agent loop.

A production-oriented reliability, benchmarking, and evaluation system that layers multi-version protocol negotiation, adaptive streaming, connection pooling, and resilience onto an MCP agent runtime.

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

An MCP server that lets an agent read its own eval results, run suites, explain failures, check drift, and view judge calibration status.

Identifies resource-intensive processes on macOS across CPU, memory, and network usage, with tools for detailed process filtering and system overview.

Enables AI assistants to monitor, analyze, and configure OWASP ModSecurity CRS via Docker, with tools for overview, drill-down, and rule/IP management.

Enables querying a self-hosted Plausible Analytics instance to retrieve compressed analytics data such as overview stats, top pages, traffic sources, and trends, with computed deltas and human-readable filters.

Ships only the MCP server, not the recorder. Recording works by wrapping a process on the host — a local proxy, a PATH shim, a shadow git index. None of that survives a container boundary, so orca record inside here would watch an empty namespace. What does travel is the read side: the six MCP tools serve runs that already exist on disk, so a client mounts its .orca directory and r

A stdio MCP server that connects directly to a Scouter Collector over TCP and queries XLogs, counters, and objects. Its purpose is to let an AI quickly explore Scouter metrics and diagnose root causes.

A read-only MCP server that exposes Azure incident-investigation tools for a single App Service and its Application Insights telemetry, enabling an agent to correlate deployment history, platform metrics, and transaction traces.

The MCP server provides an interface to the Datadog API, enabling seamless management of incidents, monitoring, logs, dashboards, metrics, traces, and hosts. Its extensible design allows easy integration of additional Datadog APIs for future expansions.

Enables an LLM client to scan Windows event log files (EVTX) for suspicious activity using Hayabusa, and browse its detection rules directly in conversation.

Exposes an observability REST API as MCP tools, enabling incident investigation through automated correlation of deploys with errors, log and metrics queries.

MCP server providing lossless file reads with deduplication, per-repo token metering, and HMAC-signed context receipts. Enables auditable, vendor-neutral measurement of what an AI agent saw.

An MCP server that enables natural language querying and troubleshooting of Kubernetes clusters, supporting multi-cluster switching and providing tools for pods, nodes, events, and logs.

RSigma is a Rust detection-engineering toolkit for the Sigma standard. Its MCP server (rsigma mcp serve) exposes the toolchain to AI agents over stdio or Streamable HTTP, with tools to author, lint, validate, and convert Sigma rules, evaluate and explain detections against log events, and inspect correlation state.

Enables read-only querying of Grafana Loki logs through tools like label discovery, LogQL queries, and recent log retrieval, without requiring knowledge of the Loki API.