"Information about 'Pusher' - Possible Meanings or Applications" matching MCP servers:

Enables agents to get fast, calibrated probabilistic answers from Jev (Typesafe AI) to yes/no, scale, or choice questions about provided material, without using a generative model.

An improved implementation of persistent memory using a local knowledge graph with a customizable --memory-path. This lets Claude remember information about the user across chats.

Enables AI agents to capture and analyze screenshots of macOS applications, windows, or the entire screen using local (Ollama) or cloud-based AI vision models, with non-intrusive, fast screen capture via Apple's ScreenCaptureKit.

An MCP server that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.

An MCP server that answers typed noul/choice/score questions about a given state with probability distributions and confidence, for routing, escalation, and gating decisions. It runs on pluggable backends (local Needle 3 or Laya models, or any OpenAI-compatible endpoint) and logs every decision so recorded ground truth can be used to track calibration.

Judgment calls on small, fast, cheap models: yes/no, pick-one and rating questions about any text, answered YES, NO or UNSURE. Four tools (likely, classify, rate, each) for TypeSafe's Jev, open models on Ollaya, Ollama or a local NLI model.

This MCP server provides persistent memory integration for chat applications by utilizing a local knowledge graph to remember user information across interactions.

A foundation for building interactive applications using the Model Context Protocol that integrates AI capabilities with Magic UI components.

Enables AI agents to control Windows desktop applications by wrapping Codex's Computer Use capability.

A Model Context Protocol server that converts Markdown content into interactive mindmaps, allowing AI assistants to visualize hierarchical information through either HTML content or saved files.

A flexible memory system for AI applications that supports multiple LLM providers and can be used either as an MCP server or as a direct library integration, enabling autonomous memory management without explicit commands.

A TypeScript server implementing the Model Context Protocol that provides secure code execution in isolated Docker containers, allowing LLM applications to safely run Python, Go, or JavaScript code snippets.

A durable DAG-based task planner exposed as an MCP server that lets AI orchestrators break a goal into a dependency graph of tasks, execute them in parallel where possible, track state durably, and handle human-in-the-loop approval through 22 MCP tools.

General purpose toolbox for AI applications

Enables cleaning and sanitizing prompts through an LLM-powered tool that removes sensitive information, provides structured feedback with notes and risks, and normalizes prompt formatting. Supports configurable local or remote OpenAI-compatible APIs with automatic secret redaction.

An MCP server that enables LLMs to 'see' what's happening in browser-based games and applications through vectorized canvas visualization and debug information.

Enables autonomous multi-turn negotiation by calculating the Zone of Possible Agreement, modeling concession decay curves, enforcing reservation price thresholds, and generating structured bargaining counter-offers. It supports agentic commerce and contract negotiation workflows through a native MCP interface.

An MCP server that translates human GUI actions into machine-executable commands, enabling AI agents to control real software applications like Zoom, Excel, and WeChat via natural language or API calls.

Coordinates specialized agents (Architecture, Quality, Cloud, Prompt) to plan, build, test, and deploy applications with self-healing capabilities, authentication, and analytics for autonomous software engineering workflows.

Model Context Protocol server that standardizes tool discovery, execution, and context management for AI applications.

Enables AI agents to safely operate Express applications through a permission-scoped MCP server, with static analysis and audit logging.

Enables asynchronous two-way messaging between Codex Desktop tasks and Claude Desktop Code sessions on Windows, allowing either side to share information, questions, or updates through MCP tools.

Enhances LLM applications with deep autonomous web research capabilities, delivering higher quality information than standard search tools by exploring and validating numerous trusted sources.

Enables an LLM to drive a real browser by declaring one outcome at a time, while Jev chooses the element, action, and value and Playwright executes it, returning a clear status such as done, blocked, or needs confirmation. Also exposes tools to open pages, ask yes/no or multiple-choice questions about a page, read question-relevant page text, capture snapshots and screenshots, act on elements directly, and invoke a page's own WebMCP tools.

A Model Context Protocol server that enables remote connections with GitHub authentication, allowing users to build applications that leverage MCP tools with secure OAuth-based access control.

MCP server providing AI-friendly computer-use primitives (capture, detect, click) to let LLM agents drive desktop GUI applications on Windows, macOS, and Linux.

An MCP server that enables LLMs to autonomously reverse engineer applications through Cutter, allowing them to decompile binaries, analyze code, and rename methods programmatically.

Safety-first Model Context Protocol platform for AEC applications, enabling AI assistants to inspect, plan, validate, and modify engineering documents after policy and approval checks.

Bridges Kimi Code CLI to OpenAI Computer Use, enabling Kimi to control local macOS applications via MCP.

A high-performance Model Context Protocol (MCP) server designed for large language models, enabling real-time communication between AI models and applications with support for session management and intelligent tool registration.