Endor
Instant, private, sandboxed environments for popular services with seamless AI agent integration.
Key Features
Use Cases
README
Endor
Endor provides instant, private, sandboxed environments for your favorite services anywhere Node is available. Run MariaDB, PostgreSQL and many more servers securely and in just a few seconds. Nothing extra to install, everything runs locally. Perfect for AI agents and humans in a hurry.
Each service will run in an ephemeral, isolated VM that only exposes the application ports. When you are done, you can exit Endor with CTRL+C and everything is gone without leaving a trace in your system.
MCP mode allows the services to be launched and used from AI tools like agents and IDEs. Your agents can now securely and safely launch database servers or KV stores as part of their capabilities!
An experimental full-networking mode can be optionally enabled, allowing you to run a fully-featured Alpine Linux machine.
Need a MariaDB database? Just type endor run mariadb. Claude Code wants to run a Valkey instance? Just run endor mcp.
Learn more in the official documentation.
Get started
Install Endor:
npm install -g @endorhq/cli
Run your first service:
endor run mariadb
You can also run the service without installing the CLI with npx:
npx -y @endorhq/cli run mariadb
Supported applications
- Alpine
- MariaDB
- Memcached
- Redis
- Postgres
- RabbitMQ
- Valkey
Connect to your AI agents
Endor connects to your AI agents using the Model Context Protocol (MCP). You can run it directly using npx:
npx -y @endorhq/cli mcp
Follow these guides to configure your favorite agent tools:
License
By using Endor, you accept our End-User License Agreement (EULA).
Star History
Repository Owner
Organization
Repository Details
Tags
Join Our Newsletter
Stay updated with the latest AI tools, news, and offers by subscribing to our weekly newsletter.
Related MCPs
Discover similar Model Context Protocol servers
VideoDB Agent Toolkit
AI Agent toolkit that exposes VideoDB context to LLMs with MCP support
VideoDB Agent Toolkit provides tools for exposing VideoDB context to large language models (LLMs) and agents, enabling integration with AI-driven IDEs and chat agents. It automates context generation, metadata management, and discoverability by offering structured context files like llms.txt and llms-full.txt, and standardized access via the Model Context Protocol (MCP). The toolkit ensures synchronization of SDK versions, comprehensive documentation, and best practices for seamless AI-powered workflows.
- ⭐ 43
- MCP
- video-db/agent-toolkit
dbt MCP Server
Bridge dbt projects and AI agents with rich project context.
dbt MCP Server provides an implementation of the Model Context Protocol for dbt projects, enabling seamless integration between dbt and AI agents. It allows agents to access and understand the context of dbt Core, dbt Fusion, and dbt Platform projects. The tool supports connection to external AI products and offers resources for building custom agents. Documentation and examples are provided to facilitate adoption and integration.
- ⭐ 420
- MCP
- dbt-labs/dbt-mcp
Defang
Develop Once, Deploy Anywhere.
Defang provides a command-line interface (CLI) and Model Context Protocol (MCP) Server that enable seamless deployment of applications from local development environments to the cloud. It supports integration with popular IDEs such as VS Code, Cursor, Windsurf, and Claude, allowing users to manage and deploy their workflows efficiently. Defang delivers secure, scalable deployments with built-in support for Docker Compose and Pulumi, and offers samples for Golang, Python, and Node.js projects. Its AI-powered features enable developers to generate and launch cloud services effortlessly.
- ⭐ 144
- MCP
- DefangLabs/defang
Flowcore Platform MCP Server
A standardized MCP server for managing and interacting with Flowcore Platform resources.
Flowcore Platform MCP Server provides an implementation of the Model Context Protocol (MCP) for seamless interaction and management of Flowcore resources. It enables AI assistants to query and control the Flowcore Platform using a structured API, allowing for enhanced context handling and data access. The server supports easy deployment with npx, npm, or Bun and requires user authentication using Flowcore credentials.
- ⭐ 9
- MCP
- flowcore-io/mcp-flowcore-platform
Postmancer
A standalone MCP server for API testing and management via AI assistants.
Postmancer is a Model Context Protocol (MCP) server designed to facilitate API testing and management through natural language interactions with AI assistants. It enables HTTP requests, organizes API endpoints into collections, and provides tools for managing environment variables, authentication, and request history. Postmancer is particularly aimed at integrating with AI platforms like Claude for seamless, automated API workflows.
- ⭐ 28
- MCP
- hijaz/postmancer
Mindpilot MCP
Visualize and understand code structures with on-demand diagrams for AI coding assistants.
Mindpilot MCP provides AI coding agents with the capability to visualize, analyze, and understand complex codebases through interactive diagrams. It operates as a Model Context Protocol (MCP) server, enabling seamless integration with multiple development environments such as VS Code, Cursor, Windsurf, Zed, and Claude Code. Mindpilot ensures local processing for privacy, supports multi-client connections, and offers robust configuration options for server operation and data management. Users can export diagrams and adjust analytics settings for improved user control.
- ⭐ 61
- MCP
- abrinsmead/mindpilot-mcp
Didn't find tool you were looking for?