"Creating a voice AI for making outbound calls via SIP telephony" matching MCP servers:

Voice Mode for Claude Code

MCP server that gives AI agents isolated, named Linux computers with stable IDs and lifecycle control. Supports multiple backends like Docker, Fly Machines, Modal, and E2B, with a dashboard for managing sandboxes.

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

Enables AI agents to invoke a local Stata installation, including a Windows Stata build under Wine on Linux and macOS, for regression analysis, econometrics, paper replication, and empirical research with command guards, resource monitoring, and automatic log capture.

Enables Large Language Models to access and manipulate Autodesk Revit models through a pyRevit-based bridge and the Model Context Protocol.

Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.

Remote-control Unity Editor from any AI IDE via file-based IPC — 62 tools, zero dependencies

Enables AI agents to program MicroPython boards such as Raspberry Pi Pico and ESP32 through Thonny, with visible shell commands and optional human approval.

Enables AI agents to observe and control a browser-based 2D robot simulator, including driving, configuring sensors and modules, running programs, and generating wiring, firmware, and parts lists for ESP32, Arduino Uno, or Raspberry Pi.

Stop stitching context for Copilot and Cursor. With Sequa MCP, your AI tools know your entire codebase and docs out of the box.

A multi-task MCP server for AI code optimization and testing that integrates with VSCode/Cursor, CLI tools, and autonomous agents. It provides tools for running tests, generating code improvements, and managing objectives across different environments.

MCP server for AI-driven CAD operations, enabling parametric modeling, build, inspection, measurement, rendering, and diff comparison with STEP, DXF, and GLB export.

MCP server for secure, session-based Python code execution in Docker containers, enabling LLM applications to run code, manage state, and access files.

Enables AI-native statistical analysis and reproducible research workflows through MCP, including natural language planning, protocol-based analysis, Python/R cross-validation, and publication-ready figure generation.

An MCP server that exposes 252 algorithms from Knuth's TAOCP to AI agents, with safety guards and structured outputs for tasks like combinatorial generation, SAT solving, number theory, string analysis, graph algorithms, and symbolic math.

A starter template for creating MCP servers that work with Puch AI, featuring ready-to-use tools for job searching and image processing. Includes examples for Bearer token authentication, OAuth integration with Google and GitHub, and demonstrates user-scoped data management.

A Model Context Protocol (MCP) server that supports STDIO, SSE and Streamable HTTP protocols for AI model interactions.

MCP server for portable context management across AI assistants, providing tools to store and retrieve persistent context, instructions, and execute sandboxed bash commands with automatic git commits, using OAuth 2.1 and magic link authentication.

Enable Claude (or any other LLM) to interactively debug your code (set breakpoints and evaluate expressions in stack frame). It's language-agnostic, assuming debugger console support and valid launch.json for debugging in VSCode.

Provides a secure workspace for AI-driven file management and Python script execution designed to run on Vercel. It enables tools for full file operations and code execution within a sandboxed environment.

Enables AI-powered coding assistance including file editing, code generation, explanation, review, and shell command execution, using multiple free AI providers with automatic fallback.

Enables LLMs to drive Blender through socket-based two-way communication, letting them create and modify 3D objects, apply materials, run Blender Python, and fetch or generate assets while visually verifying results. Supports prompt-assisted 3D modeling, scene creation, and manipulation.

Enables AI models to dynamically create and execute their own custom tools through a meta-function architecture, supporting JavaScript, Python, and Shell runtimes with sandboxed security and human approval flows.

Provides web search and code execution capabilities using OpenAI models, with optional code interpreter and conversation continuity via response IDs.

Provides emergency coding assistance by querying three AI coding models simultaneously through OpenRouter, with automatic premium fallback on rate limits, returning multiple expert opinions with cost and latency telemetry for debugging and problem-solving.

Gives AI coding agents typed, mode-gated access to a real WordPress site — content, media, users and settings via core REST, plus PHP execution, SQL queries, filesystem operations and Elementor page read/build/patch/snapshot via a companion bridge plugin. Destructive actions and code execution are guarded by feature flags, explicit confirm literals, dry runs, redaction and audit logging.

A template for creating custom tools for Cursor IDE using Model Context Protocol that allows users to deploy their own MCP server to Heroku and connect it to Cursor IDE.

A CLI tool that runs a Model Context Protocol server over stdio, enabling interaction with specification documents like business requirements, product requirements, and user stories for the Specif-ai platform.

A template for creating and connecting custom tools to Cursor IDE using Model Context Protocol with support for cheerful server responses.

A simple template for creating custom tools for Cursor IDE using Model Context Protocol, deployable via Heroku, Docker, or directly within Cursor IDE.