What commands does the server support?
The MCP server supports three commands: `ping`, `pong`, and `count`. The sample output shows `ping` returns `pong`, `pong` returns `ping`, and `count` returns the current count (e.g., `2`).
@kimtth
Basic information
🏓 An experimental and educational script for Ping-pong server demonstrating remote MCP (Model Context Protocol) calls
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"mcp-fastapi-ping-pong": {
"command": "python",
"args": [
"mcp-api-server.py"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
An experimental and educational Ping-Pong server that demonstrates MCP (Model Context Protocol) calls through a FastAPI/FastMCP backend. It provides a simple command‑handling system (ping, pong, count) accessible via API endpoints or Server‑Sent Events (SSE), making it a learning tool for understanding remote MCP integrations.
Install dependencies with poetry install. Run python mcp-api-server.py to start the FastAPI server on http://localhost:8080 and open mcp-api-client.html in a browser for the UI, or use the API directly. For SSE transport, run python mcp-sse-server.py and then python mcp-sse-client.py to interact via the command line with commands like ping, pong, and count.
The MCP server supports three commands: `ping`, `pong`, and `count`. The sample output shows `ping` returns `pong`, `pong` returns `ping`, and `count` returns the current count (e.g., `2`).
Install dependencies with `poetry install`. For the API server, run `python mcp-api-server.py`. For SSE, run `python mcp-sse-server.py`. The client for SSE is started with `python mcp-sse-client.py`.
Yes, the repository includes `mcp-api-client.html` which you can open in a browser to interact with the API server via a simple UI.
Two transport methods are demonstrated: HTTP API (GET/POST endpoints at `http://localhost:8080`) and Server-Sent Events (SSE) using separate server and client scripts.
All Python dependencies are managed via Poetry. The key libraries include FastAPI and FastMCP (for the backend), along with other runtime dependencies listed in the `pyproject.toml` file.

Know when your AI agents, cron jobs and CI pipelines fail, stall or go quiet. Your agent sets up monitors from a plain description, tells you what is broken and why, reads run history and traces, and writes notes on inci
Query your team's drift, vulnerability, and migration data from any AI assistant. Vibgrate MCP connects Cursor, Claude, ChatGPT, Windsurf, or VS Code to Vibgrate Cloud: 51 tools for DriftScores, CVEs and EOL runtimes, up
MCP server that lets Claude Code, Cursor or Codex ask you for API keys on a local page and write them to .env. The agent only ever sees key names.

Local-first credential broker for MCP. AI coding agents (Claude Code, Cursor, Codex…) call APIs, SSH and databases through scoped presets; secrets stay in your OS keychain and never enter the agent's context.
Modelglass turns "which model should I use?" into a lookup instead of a guess. Seven tools give your agent live pricing across image, language, video, and audio models. Sourced and versioned, not scraped once and forgott
Comments