"How to export LLM chat history from multiple domains" matching MCP servers:

Enables MCP clients to record, browse, read, aggregate, and delete time-series SCADA values addressed by UNS id through a broker-mediated history slot, with per-id broker capability checks and auditing. Backends are pluggable (in-memory today, with SQLite, DuckDB, and MySQL planned) behind a single store contract that a conformance suite validates.

Enables LLMs to read and analyze Spark History Server data, including jobs, stages, executors, and SQL executions, to diagnose failures and optimize performance.

A Model Context Protocol server that enables AI tools to automatically log their activities with detailed metrics like timestamps, token usage, and costs into daily markdown worklog files.

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 check remaining Anthropic and OpenAI rate-limit quotas with reset times, plus Hermes Agent token usage, so bots can throttle or stop before hitting limits.

Measured latency and uptime for 45 hosted AI inference APIs: independent probes from 4 regions every 5 minutes, no gateway. Exposes get_ai_api_latency (TTFB p50/p95 and uptime rankings by region). Data CC BY 4.0.

LLM cost optimization and provider usage visibility for MCP-capable agents.

Enables benchmarking of Large Language Model APIs by measuring performance metrics such as generation throughput, prompt throughput, and Time To First Token (TTFT) with configurable concurrency levels and parameters.

Exposes Spark History Server metrics and metadata as tools for LLM-based analysis of Spark applications. It enables deep optimization of Spark jobs by providing access to job summaries, stage details, SQL execution plans, and executor performance.

MCP server for Tessera's LLM cost-optimization layer. Anchored spend, drift detection, recommendations as typed tools.

Connect AI agents like Claude, Cursor, and Gemini to historical Windows performance and privacy data gathered by the AppControl Windows app. This server enables natural language queries into CPU, GPU, and temperature history alongside system security events for deep local auditing.

An MCP server that functions as an intelligent gateway for multiple LLM backends including OpenAI, Claude, and Ollama. It supports automatic provider fallback, streaming responses via Server-Sent Events, and real-time monitoring for robust AI integration.

A MCP server for tracking AI usage metrics and structured logs across applications. Monitor model calls, analyze usage patterns, track costs, and debug AI interactions.

Exposes Apigee X / GCP Management API operations as tools, enabling management of API proxies, environments, analytics, developers, apps, and API products through natural language commands.

Unofficial MCP server for Vexo analytics. Enables querying event names, counts, timelines, sessions, and recent events from Vexo Export API through natural language.

Enables LLM agents to query real-time and historical analytics from WireBoard, allowing natural language questions about visitors, events, and site metrics.

Daily-refreshed Glama TDQS score tracker for any MCP fleet. Scrapes per-tool grades from glama.ai, stores in SQLite with snapshot history and delta tracking, surfaces via MCP tools, Prefab cards, a 6-page web dashboard, and an LLM-powered chat interface.

Controls Unity ML-Agents training runs from Claude Code, enabling launch, stop, resume, monitor, compare, and export via natural language.

MCP server for managing Duplicati backups from an LLM.

Enables MCP-capable AI clients to search ClickHouse logs, browse instances, databases, and tables, and inspect log histograms directly from a chat.