MCP Server
Enables text-to-speech conversion via the ElevenLabs API, exposed as the textToSpeech MCP tool.
Provides a LangChain agent that orchestrates tools like getWeather and addNumbers, enabling natural language interactions via the assist tool.
Uses OpenAI's language models through the LangChain agent to process and respond to natural language queries in the assist tool.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP ServerWhat is the weather in London?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP server · TypeScript · LangChain
Minimal Model Context Protocol server in TypeScript with a LangChain / OpenAI assistant behind an MCP entrypoint (assist), plus thin tools for deterministic JSON (getWeather, addNumbers) and a TTS helper (textToSpeech). Exposes MCP over stdio (stdin/stdout JSON-RPC)—not Express/HTTP—for hosts like Cursor, Claude Desktop, or custom clients.
Why this repo
Demonstrates integrating external LLM tooling with a narrow MCP surface:
MCP stdio transport + Zod-typed tool inputs
Server-side routing: one NL entrypoint (
assist) runs an internal agent; no extra “routing” tools on the wireLangChain
createAgentwith small domain tools (weather via Open-Meteo, math helpers)TypeScript strict mode,
tscbuild todist/, demo scripts viatsx
Related MCP server: FastMCP Demo
Quick start
git clone <your-fork-url>
cd mcp-server
nvm use # optional; reads .nvmrc (Node 20)
npm install
cp .env.example .env # set OPENAI_API_KEY for assist
npm run build
npm start # MCP on stdio (after pre-build)Try the bundled demos (they build first, then spawn dist/mcp/index.js):
npm run chat -- "What is the weather in London? One short sentence."
npm run mcp:demo-client -- assist '{"message":"What is the weather in London? One short sentence."}'Architecture
flowchart LR
Host[MCP host] -->|stdio JSON-RPC| MCP[MCP server]
MCP --> assist["tool: assist"]
MCP --> getWeather["tool: getWeather"]
MCP --> addNumbers["tool: addNumbers"]
MCP --> textToSpeech["tool: textToSpeech (optional)"]
assist --> Agent[LangChain agent + OpenAI]
Agent --> W[Weather tool]
Agent --> M[Math tools]
getWeather --> API[Open-Meteo / geocoding]Design choices
Hosts should send natural language through assist so prompts, tool boundaries, and model config stay on your machine. Structured integrations can call getWeather or addNumbers directly when inputs are already known (no NL).
MCP tool | Purpose |
| Default. |
| Raw JSON for a known city (Open-Meteo, no API key). |
| Raw JSON sum of two numbers. |
| Text → MP3 audio (MCP audio + metadata). |
OPENAI_API_KEY must be visible to the MCP server process for assist (e.g. .env loaded from dotenv, or env vars in your host’s MCP config—never commit secrets).
Layout
Path | Role |
| MCP server bootstrap, stdio transport. |
| NL → |
| Thin MCP tools. |
| Registry, |
| HTTP/domain helpers (weather, math). |
| Example host (LangChain + |
| Raw MCP SDK client demo. |
npm run build emits dist/ (listed in .gitignore).
Commands
Script | What it does (demo/testing) |
| Compile with |
| Same as |
| Build (prestart), then |
|
|
| Demo host running the whole agent system via MCP |
| Demo/testing MCP client. Call tools individually (e.g. |
| ElevenLabs TTS smoke test (needs |
Examples: run everything vs tools only
Run the whole agent system (natural language → assist → internal LangChain agent → final text):
npm run chat -- "What is the weather in London? How is 34+7?"Same flow, but calling assist explicitly with an object payload:
npm run mcp:demo-client -- assist '{"message":"What is the weather in London? How is 34+7?"}'Testing individual MCP tools (not required for the full agent):
npm run mcp:demo-client -- getWeather '{"city":"London"}'
npm run mcp:demo-client -- addNumbers '{"a":34,"b":7}'
npm run mcp:demo-client -- textToSpeech '{"text":"Hello from the server"}'Cursor & Inspector
After npm run build, point the host at node /absolute/path/to/dist/mcp/index.js.
MCP Inspector: npx -y @modelcontextprotocol/inspector node dist/mcp/index.js from the repo root. Pass assist secrets with -e OPENAI_API_KEY=$OPENAI_API_KEY where needed.
FFmpeg and ffplay (optional)
The npm run speak script can play MP3 in the terminal using ffplay, which ships with FFmpeg. If ffplay is not on your PATH, the script still works by saving a short MP3 under your temp folder and opening it with the OS default app; install FFmpeg when you want in-terminal playback without that fallback.
Windows
winget (built into Windows 10/11):
winget install --id Gyan.FFmpeg --source winget --accept-package-agreements --accept-source-agreementsClose and reopen your terminal (or Cursor’s integrated terminal) so the updated PATH includes the FFmpeg
bindirectory.Confirm
ffplayis visible:ffplay -version
If ffplay is still not found, add the folder that contains ffplay.exe manually: Settings → System → About → Advanced system settings → Environment Variables → Path → Edit → New (typical install paths look like C:\ffmpeg\bin or under %LOCALAPPDATA%\Microsoft\WinGet\Packages\…).
Manual download: gyan.dev FFmpeg builds (full or essentials build), unzip, then add the bin folder to PATH as above.
macOS
brew install ffmpeg
ffplay -versionLinux (Debian / Ubuntu example)
sudo apt update && sudo apt install -y ffmpeg
ffplay -versionOther distributions: install the ffmpeg package from your package manager; ffplay is included in the same package.
Contributing
Issues and PRs welcome. Extend internal agents via src/agents/ and assist.ts routing if you split personas.
Checklist before you promote the repo
Set
authorand (optionally)repository/homepage/bugsinpackage.jsonso npm and GitHub link correctly.Replace
OWNER/REPOin the commented CI badge when the remote exists, then uncomment the line.Add a GitHub profile README or link this repo from your CV/LinkedIn—recruiters land here first from the link.
Set the repo About description and topics (e.g.
mcp,langchain,typescript,ai-agents).
License
ISC — see LICENSE.
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