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

An MCP server that enables AI applications to access 20+ model providers (including OpenAI, Anthropic, Google) through a unified interface for text and image generation.

Just to be clear about the final JSON: the MCP server is named herdr-inbox, and it enables Claude Code agents in herdr to ask questions asynchronously without stalling, with all open questions answered from one popup and answers routed back to the asking agent.

Provides AI assistants with real-time access to the AGNO framework documentation by enabling them to browse, search, and fetch documentation pages. This server allows users to query information about AGNO's Agents, Teams, and Workflows directly through MCP-compatible clients.

A Model Context Protocol server that enables scalable mobile automation for iOS and Android through a platform-agnostic interface, allowing LLMs to interact with mobile applications via accessibility snapshots or screenshot-based inputs.

Authenticates with Databricks via OAuth and exposes remote MCP tools from Databricks applications, enabling interaction with Databricks-hosted tools through Claude.

Enables selecting a saved Codex or Claude Code session from the same PC and importing its recent context into the other tool, so work can continue across clients with source and omission information.

Enables AI agents to control legacy web applications running in Microsoft Edge's IE Mode via MCP, using Selenium WebDriver and IEDriverServer for browser automation.

A Model Context Protocol server that enables scalable mobile automation through a platform-agnostic interface for iOS and Android devices, allowing agents and LLMs to interact with mobile applications using accessibility snapshots or coordinate-based interactions.

Enables agents to crawl and read websites politely, learning per host which reader, URL rewrite, or detail path actually reaches good information, and reusing those wins across runs or a shared database. Failures come back as coded errors with concrete next steps, so blocked or empty pages point to an honest alternative instead of endless retries.

A persistent memory implementation using a local knowledge graph that lets Claude remember information about users across conversations.

The AgentOps MCP server provides access to observability and tracing data for debugging complex AI agent runs. This adds crucial context about where the AI agent succeeds or fails.

Enables Claude Code and Gemini CLI to see your macOS screen, answering questions about the file, error, UI, database table, or web page you're looking at. Captures screenshots, reads database schemas, and controls Chrome/Brave, presenting answers as on-screen highlights or spoken bubbles above your cursor.

Enables deploying applications and managing cloud resources in Timeweb Cloud through natural language.

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.

A ready-to-use starter implementation of the Model Context Protocol (MCP) server that enables applications to provide standardized context for LLMs with sample resources, tools, and prompts.

A Model Context Protocol server that allows AI applications to interact with Crawlab's functionality through natural language, enabling spider management, task execution, and file operations.

Drive Clearcote, a Chromium build with its fingerprint protection patched into the engine, from any MCP client: about 20 tools to navigate, read, extract, click, fill, screenshot and keep sessions, plus a CDP endpoint that hands the same browser to Playwright or Puppeteer. The server lives in the repo's mcp/ folder (npx clearcote-mcp or pip install clearcote-mcp).

A comprehensive Model Context Protocol (MCP) server suite that enables AI coding agents to automate both web browsers and Electron desktop applications with auto-snapshots and element references.

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.

Keeps large tool outputs out of an agent's context window by spilling them to disk and handing back a short pointer instead. Lets the agent pull only what it needs — exact numbered line ranges read directly from disk, or verbatim relevant lines returned by a small model answering a question about the stored output, plus tools to open, list, and close documents.

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 connects AI assistants with the Kernel platform, enabling them to deploy applications, automate web browsers, and manage cloud resources.

Enables external AI applications to access MCP tools by providing a user-hosted HTTPS endpoint that forwards requests to a paired desktop client.

A server that enables AI models to access user geolocation information via EdgeOne Pages Functions through the Model Context Protocol.

A transparent message ferry between Claude Desktop and Claude Code CLI, enabling task delegation with any MCP configuration without the bridge needing to know about specific MCPs.

Bounded egress gateway & secret proxy for AI agents and applications, enabling safe credential injection into upstream requests while keeping raw secrets out of LLM prompt contexts.

Enables agents to connect from different applications and machines, register themselves, publish nested live context and visualizations such as metrics, charts, tables, logs, plans, and diffs, send heartbeats, and archive their state through MCP over Streamable HTTP.

Enables MCP-compatible applications to manage and use local or cloud LLM models through comprehensive SDK tools, including model management, text generation, chat with tool support, embeddings, and web search/fetch.

Coordinates specialized agents (Architecture, Quality, Cloud, Prompt) to autonomously plan, build, test, and deploy applications with self-healing capabilities, authentication via Descope, and analytics through Cequence.