"Resources for Building Agentic AI" matching MCP servers:

A Model Context Protocol server that enables Claude to execute Python code using boto3 to query and manage AWS resources directly from conversations.

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.

A local MCP gateway that allows AI clients to manage and interact with multiple MCP servers through a single connection, providing token-efficient access to tools and resources.

An MCP server that gives AI agents terminal execution, Python scripting, file management, and code search tools so they can carry out real development tasks. It exposes bash, Python, glob, grep, and file/folder operations over MCP for coding assistants and codebase exploration.

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

A Model Context Protocol server providing AI assistants with comprehensive project, task, and subtask management capabilities with project-specific storage.

VS Code extension that bridges local Jupyter Notebooks with AI Agents via MCP, enabling direct control of the active notebook tab.

Gitbub mcp

Enables deployment of autonomous AI agents with memory and tool execution capabilities through a WebSocket-based MCP protocol. Provides production-ready infrastructure with REST API access, persistent state management, and extensible function registry for building self-hosted AI systems.

Enables AI agents to securely control a remote Windows/Linux PC via MCP and REST, executing shell commands and driving coding-agent CLIs like Claude, Cursor, and Codex.

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.

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

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

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.

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.