"An overview of knowledge graphs and their applications" 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.

A local MCP server that gives LLMs long-term memory by indexing code, infrastructure, logs, and docs into a queryable graph. It enables semantic and structural search, evidence-backed reasoning, and tracked plans that persist across sessions and teams.

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.

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

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

Enables precise measurement of live HTTP and WebSocket services while maintaining an append-only, evidence-based ledger of claims that agents can query with explicit timestamps, staleness indicators, and instructions for re-verification.

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.

Provides governed MCP tools for querying optionally restricted Microsoft Sentinel/Log Analytics tables and optional Defender XDR hunting data, retrieving incidents and entities, and—for agent identities only—adding attributed incident comments, with Entra ID authentication, KQL validation, rate limits, and redacted audit logging.

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.

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.

Local MCP server for Java heap dump analysis with Eclipse MAT: heap overview, histograms, dominator trees, threads, OQL, leak suspects, and OOM diagnosis.

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.

Lets coding agents read a local, redacted recording of the user's dev-browser session — pages, clicks, typed fields, API calls with their bodies, console errors and screenshots — so they can see what the user just did and what failed before asking. Exposes a recent-activity timeline tool with optional time, text and event-kind filters plus a tool that returns an individual screenshot as an image.

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.

A Model Context Protocol server that provides seamless integration with Coroot observability platform, enabling monitoring of applications, analysis of performance metrics, examination of logs and traces, and management of infrastructure through Coroot's comprehensive API.

Enables AI assistants to perform automated root-cause analysis of slow Apache Spark and Databricks jobs by listing applications, planning and running diagnoses, retrieving stage and SQL plan details, and listing diagnosis rules via read-only MCP tools.

Enables running Splunk searches and reading their results against a Splunk Cloud deployment that requires interactive Microsoft Entra SSO and MFA, using a Playwright-managed authenticated browser session instead of API tokens.

Exposes Spark History Server data as tools for AI agents, enabling natural language querying of Spark applications, jobs, stages, and performance metrics.

Enables agents to connect from different applications and machines, register themselves, publish nested live context and visualizations such as metrics, charts, tables, logs, plans, and diffs, send heartbeats, and archive their state through MCP over Streamable HTTP.