"How to use the terminal" matching MCP servers:

Screen-reader navigation cost analyzer. Measures how hard it is for assistive-technology users to discover, reach, and operate interactive targets on the web.

Semantic memory for AI builders: capture the tacit engineering know-how that never reaches your docs, recall it the moment it applies. Built in Rust on Postgres and pgvector.

Enables AI assistants to manage events, venues, organizers, and tickets on WordPress sites via CRUD operations.

AI-powered multi-voice audiobook creation platform. Provides tools for pricing, language support, use cases, onboarding, FAQ, alternatives comparison, and cost estimation. npx echo3s-mcp

Lets AI hosts answer questions about Kenda token spend and waste directly from the terminal.

An MCP server for interacting with the USAspending.gov API, supporting local use with Claude Desktop and cloud deployment with login.gov authentication.

Give any LLM agent a real Android or iPhone. 62 MCP tools: tap, swipe, type, screenshot, screen-tree reading, app launch, camera, TTS, crash reports, batched execution. Android via ADB, iPhone via WebDriverAgent, on-device inference, Docker+KVM emulators. Works with Claude Code, Cursor, LangChain, LlamaIndex, and any MCP client. MIT.

Enables LLM clients to execute shell commands safely through the MCP protocol, with features like session management, safe mode, and process control.

Enables agents to transform tabular Markdown content into structured, type-inferred records with normalized formatting through an MCP-compatible interface.

What is PandaDoc MCP? PandaDoc MCP (Model Context Protocol) server connects AI agents directly to PandaDoc's document workflow — creating, sending, and tracking contracts and agreements without leaving your AI client. How to use PandaDoc MCP? To use PandaDoc MCP, connect your PandaDoc account, provide the required API credentials, and configure the appropriate MCP client.

Enables converting Markdown and HTML tables into structured JSON records with automatic column type inference and format normalization. It also offers supporting web-agent primitives such as DOM semantic pruning, form field auto-mapping, and execution trajectory evaluation, all via a zero-dependency MCP server.

Enables AI agents to interact with The Colony social network, including posting, commenting, voting, and direct messaging.

This MCP server lets AI agents connect to Figma to read, analyze, create, and modify designs, including elements, styles, assets, and code generation. It works with free Figma accounts and supports parallel multi-agent use across MCP-compatible clients.

Enterprise-grade code intelligence server for AI assistants that analyzes codebases for due diligence, tech debt, security vulnerabilities, and code quality.

Enables AI assistants to query PostgreSQL, MySQL, SQL Server, Oracle, and MongoDB databases through MCP with read-only, audited access.

Enables agents to break high-level business objectives into dependency-ordered sub-task graphs and then directly generate the finished deliverables, such as financial spreadsheets, executive presentations, and analytical reports. It runs as a zero-dependency Python MCP server over JSON-RPC stdio, adding deterministic authorization, role-boundary validation, and telemetry.

Saves the image currently on the system clipboard to a file (PNG or JPG), enabling AI agents that cannot access the clipboard to use clipboard images.

Enables searching government awards through the Sell to State API by proxying JSON-RPC to the live HTTP MCP endpoint, requiring an API key.

An MCP server for external computer-use that launches, observes, and interacts with any X11 application via AT-SPI2 accessibility tree and xdotool input injection.

Enables AI agents to create and manage payment links programmatically via the Global Payments API, supporting single-use and multi-use links, retrieval, and API documentation retrieval.