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

Enables real-time assessment of GitHub repository health by exposing tools and resources for repository metadata, open issues, recent commits, and GitHub Actions workflow runs, plus prompts for health reports and issue triage.

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.

Monitors and analyzes GitHub repository health by detecting stale branches, old pull requests, unresponsive issues, and security alerts. Integrates with MCP-compatible AI assistants and automation tools.

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

A minimal MCP server that exposes health-check and server information tools over stdio or HTTP, and can be containerized and deployed to IBM Code Engine.

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.

Enables read-only, workspace-bound inspection of repositories and log files, returning JSON reports with file counts, largest files, TODO/FIXME markers, and warning/error counts.

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.

An intelligent MCP server that gives AI agents full control over GitHub Actions CI/CD pipelines, including real-time monitoring, log analysis, AI-powered failure diagnosis, and deployment management.

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.

An MCP server that retrieves current GitHub Copilot usage data, including quotas, limits, and usage statistics. It allows AI agents to monitor premium interaction status and detailed account usage via raw or formatted summaries.

This server integrates with GitHub Advanced Security to load security alerts and bring it into your context. Supports Dependabot Security Alerts, Secret Scanning Alerts, Code Security Alerts

Enables multi-agent system auditing with seven-layer analysis, cost governance, compliance mapping, and watchdog monitoring. Offers tools for audit execution, cost analysis, report verification, regulation lookup, remediation suggestions, and fix tracking.

Enables users to measure, track, and compare response times of GitHub Copilot and other AI models. Provides statistical analysis and performance comparison tools for evaluating AI model efficiency.

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 Microsoft Copilot Desktop and Microsoft 365 Copilot Studio to post/read Slack messages, query GitHub repository status, and monitor live pod health and fleet runtime briefs.

An MCP server for tracking and managing AI command usage history using a PostgreSQL database. It enables users to log, search, and view statistics for various AI-related commands and their execution contexts.

MCP Server for notify to telegram / weixin

Enables AI assistants to query what domains and SSL certificates are expiring soon, add and bulk-import tracked assets, trigger re-checks and view check history, manage clients, alert channels, reminders and webhooks, and generate monthly renewal reports through a hosted remote endpoint.

Monitors and analyzes GitHub repository activity (stars, commits, issues) with automated reporting. Supports AI-powered trend analysis and automatic notifications to Feishu (Lark) messaging platform.

Reads a GitHub repository's own workflow and scheduled-run history to report runs that were late, never happened, failed, or succeeded without doing anything, plus schedules GitHub has disabled and the 60-day inactivity countdown. It is read-only, uses the caller's own GitHub token, and returns a JSON report usable by an agent to verify that scheduled workflows actually ran when they should have.

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.

Shows, cron slot by cron slot, how late each scheduled GitHub Actions run started, which slots never ran, and whether your config or GitHub's scheduler is to blame; can catch up missed slots without double-running.

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

Enables agents to look up and search servers from the official MCP registry, probe any server live for availability, protocol, auth, tools and context-token cost, and retrieve registry-wide statistics. Also supplies a CLI and GitHub Action that measure how many tokens your own configured servers' tool definitions consume against a budget.

Enables MCP clients to inspect Google Play releases, reviews, Android vitals, and scoped bulk reports, and to prepare explicitly authorized changes using locally supplied service-account credentials. Reads are default, while optional writes and sensitive reads require explicit configuration and single-use execution.

An MCP server that records agent execution metrics and exposes a Context Window Explorer to visualize exactly what entered the model's context window across sessions, tokens, and tool calls.

A lightweight MCP server that enables AI assistants to execute local development tools and retrieve system status with low latency over stdio or HTTP.