"A scheduler that invokes an agent on a predefined schedule" matching MCP servers:

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

Local MCP server for A-share stock trading via Tonghuashun, offering account/position queries, buy/sell/cancel orders with risk controls and forced user confirmation; currently simulated with a reserved interface for real broker channels.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

MCP server for scheduling tasks with cron-like recurring jobs, one-time tasks, priority queues, retry logic, and job dependencies.

An MCP server for searching and downloading books from Library Genesis, supporting EPUB, MOBI, PDF, and more through natural language queries.

Enables coding agents to add a bounded semantic-judgment layer for routing, ranking, extraction, verification, and escalation, returning typed signals and review recommendations.

MCP server adapter that exposes A-share stock data tools, prompts, and resources via FastMCP, enabling querying of stocks, K-lines, financials, sectors, and market hot spots through natural language.

Codebase Q&A agent with git-history awareness. Explore a repo with list_files, read_file, and search, plus git log, blame, and diff and a repo map to answer "why did this change?" questions. Runs locally as an MCP server for Claude Code and other MCP clients.

A robust task scheduler server for scheduling and managing various types of automated tasks including shell commands, API calls, AI tasks, and reminders.

Enables AI-to-AI consultation for critical thinking and complex reasoning via OpenRouter, allowing one AI to delegate tasks to another AI model.

Exposes the Appointment Scheduler API to AI agents as an MCP server, enabling them to list users and services, check availability, book, list, and cancel appointments via natural language.

An MCP server that scrapes movie theater schedules from eiga.com to provide movie, theater, and showtime data to AI assistants. It enables users to search for screenings and calculate the optimal viewing order for watching multiple movies.

An MCP server that decides whether each step of an agent requires cheap intuition (System 1) or expensive deliberation (System 2) by learning from experience rather than hand-written rules.

An MCP server that creates calendar events for FIFA World Cup matches and sends email reminders with match details.

MCP server that defers non-urgent tasks to off-peak hours, saving ~50% on DeepSeek API costs without blocking users.

Production-ready MCP server providing RAG, hierarchical memory, and 8+ tools for AI agents via the Model Context Protocol.

Enables agents to drive a running React application through typed MCP tools, using the same actions as the UI instead of browser automation.

Enables AI agents to control a Playwright-driven browser through natural-language instructions, including page interaction and live browser task execution.

Enables users to query Chinese A-share stock data, including stock basics, historical prices, financial reports, and macroeconomic indicators.

Enables AI clients to read and write calendars, schedules, and reminders through six operations, supporting daily views, templates, completion tracking, conflict/recovery handling, and auditing.

An open source biomedical research agent that provides LLMs with 28 tools for drug discovery, protein analysis, literature search, medical imaging, omics, and sandbox execution, all running locally via Ollama and MedGemma.

Enables creation and management of scheduled tasks with interval, cron, or one-time triggers. Persists tasks in SQLite and supports MCP sampling to automatically invoke AI agents when schedules trigger.

A local-first RAG system that indexes personal documents and enables querying them via an MCP tool, keeping data private with local embeddings.

Bridges the ChatGPT web UI to a local development environment over MCP, letting the model read and patch files, run real shell commands and terminals, execute tests, and control the desktop (screen, mouse, keyboard, clipboard) within user-approved folders. It adds parallel workers, goal/loop long-task control, plugin tools, and a security-hardening layer with risk-tiered shell policy, audit logging, and credential sanitization.

Enables Claude Code, Cursor, and Codex users to orchestrate plan/build/review workflows across host or CLI models with a spec gate, tool vetting, hard per-run and per-day cost/token limits, safe defaults, and clear logs.

Connects ChatGPT to local files, terminals, and the desktop through MCP with Chrome integration, letting users read and edit project files, run commands, and follow tool results as they arrive. It also adds durable multi-agent workers, Goal/Loop task tracking, mid-task corrections, and Compact & Resume for carrying session and worker history into a fresh chat.

Enables AI agents to create, update, delete, list, and inspect OS-native scheduled tasks and their logs across Windows, Linux, and macOS through a unified interface.

Enables ChatGPT to access approved local Windows folders, run commands, control the desktop, and manage session history through a permission-bounded MCP server.

MCP server that diagnoses ML model regressions by correlating drift reports, eval runs, and deploy logs, providing evidence-cited incident reports through a set of investigation tools.