"How to call a smart contract function" matching MCP servers:

A PTY-based MCP server providing persistent, interactive shell sessions with strong Windows support, enabling AI agents to run commands, handle interactive tools, and manage large output across MCP-compatible clients.

Cross-platform command execution server that intelligently adapts shell commands to the operating system and detects project-specific package managers (npm/bun, pip/poetry), with runtime-editable command mappings per project.

Enables AI agents to control and interact with a local Windows computer through authenticated MCP tools, including file operations, shell commands, process management, HTTP requests, and system/media inspection.

Enables AI agents to securely connect to and manage remote servers via SSH, with tools for running commands, file operations, log inspection, service management, and system monitoring under configurable access controls and audit logging.

A lightweight MCP server that enables AI assistants to interact with the local machine through terminal, filesystem, and Python execution tools.

A local MCP runtime for macOS and Windows that enables ChatGPT to read, edit, search, run tests, and capture screenshots in your local project folder while keeping your source code on your machine.

Provides secure filesystem access for AI models through the Model Context Protocol with strict path validation, file operations, directory management, and system command execution within predefined directories.

A simple MCP server that exposes a terminal tool, allowing AI agents to execute shell commands.

The m2m-mcp-server-ssh-client provides a unified MCP server interface, securely connecting via SSH to the m2m-mcp-server-ssh-server back-end which aggregates MCP servers. This setup offers secure, single-point access to diverse remote tools using robust SSH key-based authentication.

An MCP server that enables AI assistants to execute shell commands and manage files on remote servers via SSH. It supports recursive directory uploads, archive extraction, and direct file creation from text content.

A self-hosted MCP server that enables AI coding agents to read, edit, search, and run code in local projects with human review loops and policy controls.

Enables MCP-compatible AI clients to connect to a Windows machine for file operations, PowerShell execution, Git inspection, task management, memory, and skills.

A single-purpose MCP server that lets an AI assistant run commands over SSH on a fixed, pre-configured host only, with an explicit per-call confirmation gate before execution.

An MCP server that lets AI assistants manage an OpenMediaVault NAS over SSH using OMV's own RPC interface, covering disks, filesystems, shares, users, S.M.A.R.T. health, services, and configuration changes. It exposes a small set of generic tools to discover and call RPC methods, plus optional shell access.

Enables AI agents to establish and manage persistent SSH sessions, supporting smart command execution, async tasks, multi-host, sudo, and file operations through SFTP.

MCP server that gives AI agents real interactive terminal sessions for running REPLs, SSH, database clients, and any interactive CLI with clean text output and smart completion detection.

Local Dev Doctor turns an unfamiliar development checkout into an evidence-backed diagnosis. It discovers how the project is meant to run, checks safe prerequisites, and executes only the exact probe that a user approves.

An MCP server that gives AI agents smart hands for physical machines, controlling them via IP-KVM, BMC, and SSH with visual boot-phase classification and operator-gated actions.

A Model Context Protocol server that enables controlling Nanoleaf smart lights through Warp terminal or any MCP-compatible client, providing tools for device discovery, authorization, and control of lights, brightness, colors, and effects.

A lightweight stdio-only MCP server that allows AI agents to run multiple tasks (e.g., Python code, HTTP requests, shell commands) in parallel or with dependencies, returning structured results in a single call.