Zapier MCP

mcpc is Apify's open-source universal command-line client for the Model Context Protocol (MCP). It maps MCP operations for tools, prompts, resources, asynchronous tasks, skills, notifications, and logging to shell commands, communicating with local stdio servers and remote Streamable HTTP servers. Persistent named sessions keep connections, caches, notifications, and authentication state available across commands. The CLI supports progressive tool discovery through grep and compact tool listings, interactive shells, JSON output for jq, xargs, and shell pipelines, schema validation for scripts and CI, OAuth 2.1 with PKCE and bearer authentication, and a local proxy mode that keeps upstream credentials and OAuth tokens outside AI sandboxes. Its single configuration and credential store can be reused by shell-based AI coding agents, with credentials stored in the operating system keychain. It is distributed as the `@apify/mcpc` npm package.

Apify MCP Server is an MCP server from Apify that lets AI assistants use Apify Actors as tools for web search, data extraction, scraping, browsing, and automation. Its hosted endpoint at mcp.apify.com supports Streamable HTTP and OAuth, while a local stdio distribution is available through the @apify/actors-mcp-server package. The server dynamically discovers Actors from the Apify Store, loads their input schemas, runs them, and exposes results through Apify datasets and key-value stores. It also provides tools for searching Apify documentation, inspecting and managing Actor runs, tasks, schedules, builds, and source files. Tool selection can be restricted through URL parameters or CLI flags, and the server supports agentic payment mechanisms including AGI, direct x402, and Skyfire.

Desktop Commander MCP is an open-source Model Context Protocol server that lets AI assistants search, read, write, move, and edit files; run terminal commands and code; and manage interactive or long-running processes. It is built on the MCP Filesystem Server and adds search-and-replace editing, streamed command output, session management, process controls, configurable timeouts, and background execution. It also supports file previews and Markdown editing, data analysis for CSV, JSON, and Excel files, and native operations on Excel, PDF, and DOCX documents. The repository documents use with Claude Desktop and other MCP clients, as well as remote AI control through ChatGPT, Claude web, and other AI services. Its associated Desktop Commander App adds a graphical interface, live file-change previews, arbitrary model support, and custom MCP configuration.

Awesome MCP Servers is a curated collection of Model Context Protocol (MCP) server implementations, maintained as a GitHub repository with a synchronized web directory. It catalogs production-ready and experimental servers that let AI models interact with local and remote resources through standardized interfaces, including file access, databases, API integrations, browser automation, cloud platforms, research services, and other contextual tools. The repository organizes entries by capability, programming language, deployment scope, operating system, and whether an implementation is official.

Model Context Protocol (MCP) is an open, standardized protocol layer for connecting large language models and AI agents with external data sources, hosted infrastructure tools, and other contextual data. It defines formats, metadata, protocol schemas, and APIs for sharing information and tools, attaching, referencing, and validating context such as documents, embeddings, and provenance, while supporting scoped authentication and permissions. MCP translates JSON requests from an agent into calls to service APIs, including CRM, container-management, and GKE capabilities, and can provide design-system context and related tools for generating consistent applications. The official project publishes its specification, documentation, and protocol schema; the schema is defined first in TypeScript and also provided as JSON Schema for broader compatibility. The protocol was created by David Soria Parra and Justin Spahr-Summers, is hosted at modelcontextprotocol.io, and is licensed under the MIT License.