"How to view GitHub repository history" matching MCP servers:

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

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

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.

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.

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

Real-time GitHub Actions observability through VS Code with GitHub Copilot, providing DevOps metrics and interactive dashboards.

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.

MCP server for monitoring health of MCP servers, GitHub Actions, GitLab pipelines, and HTTP endpoints with health history, TLS expiry, assertions, diagnostics, and alerts.

Enables AI assistants to interact with Healthchecks.io, allowing users to list, create, update, pause, resume, and delete checks, as well as view ping history and integrations.

Enables coding agents to debug backend requests by providing tools to list, view, wait for, diagnose, and clear request traces.

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

MCP server for analyzing Ascend PyTorch Profiler performance data. Enables users to identify performance bottlenecks, analyze operator time, view communication overhead, and query trace data via natural language.

MCP server to access the Zabbix API, providing tools to list hosts, problems, triggers, items, history, and events.

Compares AI coding tool spend before and after a migration -- Cursor, Claude Code, GitHub Copilot, OpenCode, Codex CLI -- via an MCP server, real numbers from each vendor's own API or local logs.

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

MCP server for AWS infrastructure analysis. Connects to DynamoDB, Lambda, SQS, SNS, Secrets Manager, EventBridge, RDS, PostgreSQL, MongoDB, and CloudWatch — surfaces missing indexes, queue DLQs, Lambda config issues, IaC drift, and security findings for Claude Code and Cursor.

Provides a set of read-only Kubernetes functions via an MCP server, enabling interaction with Kubernetes clusters through agents or coding assistants like GitHub Copilot.

Enables investigation and diagnosis of CIB Seven BPM process instances through the CIB Seven REST API. Supports querying process instances, incidents, activity history, and BPMN definitions with Keycloak authentication and configurable variable redaction.

An MCP server for debugging Temporal workflows, enabling LLM-assisted inspection of workflow executions, detailed workflow info, and event history.

Enterprise AI operator evaluation MCP server. 27 tools (22 read + 5 write) for measuring, benchmarking, diagnosing, and interv ening on how human operators use AI tools across 5 canonical metrics.