About
This lightweight MCP server demonstrates basic tool implementation with simple hello and goodbye functionality, providing a clean example for developers to learn and extend. It ships with an Agently configuration for quick setup.
Capabilities
Agently MCP Hello‑Goodbye Server
The Agently MCP Hello‑Goodbye server is a lightweight, ready‑to‑run example that showcases how to expose simple text‑based tools through the Model Context Protocol. It solves a common pain point for developers: demonstrating the mechanics of tool implementation without the overhead of complex business logic. By providing a minimal, well‑structured server, it lets teams experiment with MCP integration early in the development cycle and gain confidence that their agents can call external services reliably.
At its core, the server implements two straightforward tools—hello and goodbye. Each tool accepts a single string argument, performs a trivial transformation (capitalizing the input or appending a friendly farewell), and returns the result. The implementation follows Agently’s recommended patterns for tool definition, including clear input schemas and concise response formats. This consistency makes the server an excellent reference for building more sophisticated tools that interact with databases, APIs, or other external resources.
Key capabilities of the Hello‑Goodbye server include:
- Tool registration: The server automatically registers its two tools with the MCP broker, making them discoverable by any compatible AI assistant.
- Agent configuration: An example Agently configuration file is bundled in the directory, illustrating how to bind the tools to an agent’s skill set.
- Minimal footprint: Written in pure Python with no heavyweight dependencies, the server can be deployed locally or in a containerized environment without significant resource requirements.
- Extensibility: Developers can easily add new tools or modify existing ones by following the same pattern, ensuring that the server scales from a demo to a production‑ready service.
Typical use cases for this MCP server include:
- Rapid prototyping: Quickly spin up a tool‑enabled agent to validate conversational flows before integrating complex APIs.
- Educational demonstrations: Use the server in workshops or tutorials to illustrate MCP concepts such as tool discovery, invocation, and response handling.
- Testing pipelines: Integrate the server into CI/CD workflows to verify that agents correctly parse and execute tool calls under various scenarios.
Integration with AI workflows is seamless. Once the server is running, any MCP‑compatible assistant can query its tool registry, select hello or goodbye, and pass arguments directly from the conversation context. The assistant receives a structured response, allowing it to incorporate the output into subsequent dialogue turns or trigger downstream actions.
The standout advantage of the Agently Hello‑Goodbye server lies in its simplicity coupled with adherence to best practices. It removes the barrier of learning MCP tooling by providing a clean, documented example that developers can copy, modify, and extend. This foundation accelerates the transition from concept to fully functional AI‑powered applications that leverage external tools for enriched user experiences.
Related Servers
MindsDB MCP Server
Unified AI-driven data query across all sources
Homebrew Legacy Server
Legacy Homebrew repository split into core formulae and package manager
Daytona
Secure, elastic sandbox infrastructure for AI code execution
SafeLine WAF Server
Secure your web apps with a self‑hosted reverse‑proxy firewall
mediar-ai/screenpipe
MCP Server: mediar-ai/screenpipe
Skyvern
MCP Server: Skyvern
Weekly Views
Server Health
Information
Explore More Servers
Enjin Platform MCP Server
Interact with Enjin Platform API from your IDE
Worker17
Lightweight background task executor for AI workloads
MCP API Connect
Connect to any REST API with a single command
Mindmap MCP Server
Convert Markdown to interactive mind maps in minutes
Email MCP
Add email send/receive to AI agents
Chatwork MCP Server
Control Chatwork via AI with Model Context Protocol