MCP Voice Client
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 Voice ClientWhat is my copay?"
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 Voice Client
Barebones MCP server + a web voice client. Tap a mic button in your browser, speak a command, and see the raw MCP tool response.
Voice → Web Speech API → transcript → OpenAI (function calling)
→ picks MCP tool + args → MCP server → response → UIStructure
server/main.py # FastMCP server: add, echo tools + greeting resource
client/main.py # CLI client (original)
client/web.py # FastAPI web client backend
client/static/index.html # Voice UI (mic button + response cards)
pyproject.toml
.env.exampleRelated MCP server: openapi-to-mcp
Setup
uv sync
cp .env.example .env
# edit .env and paste a fresh OPENAI_API_KEYRun
Terminal 1 — MCP server:
uv run python -m server.mainTerminal 2 — web voice client:
uv run python -m client.webOpen http://127.0.0.1:5173 in Chrome (Web Speech API requires Chromium-based browsers). Tap the mic, say a command:
"add two and three"
"echo hello world"
Response card shows: transcript, tool chosen, arguments, and the raw MCP response.
CLI variant (no UI)
uv run python -m client.mainSecurity note
.env is gitignored. Never commit or paste your API key in chat — rotate it at https://platform.openai.com/api-keys if you do.
Extend
Add a tool: decorate a function with
@mcp.tool()inserver/main.py. The web UI picks it up automatically on the next request (tools are listed fresh each call).Swap the LLM model: change
gpt-4o-miniinclient/web.py.
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