@prosodyai/mcp-docs
OfficialClick 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., "@@prosodyai/mcp-docsshow me the TypeScript quickstart recipe"
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.
@prosodyai/mcp-docs
MCP server that exposes ProsodyAI documentation, SDK references, REST API reference (OpenAPI), and curated implementation recipes to AI coding agents.
Built so that an external coding agent (e.g. AureliaStudio) can implement ProsodyAI integrations correctly the first time, without scraping the website or guessing API shapes.
Ships with two transports in a single TypeScript codebase:
stdio — for local agents (Cursor, Claude Code, Cline, etc.)
HTTP (Streamable HTTP) — for remote/hosted agents
Tools exposed
Tool | Purpose |
| Search docs, SDK READMEs, recipes, and OpenAPI in one call |
| Browse everything by section ( |
| Fetch the full body of a doc / README / recipe by id |
| List end-to-end implementation guides |
| List REST endpoints from the bundled OpenAPI spec, filterable by tag |
| Full OpenAPI operation object for a single endpoint |
| The entire bundled OpenAPI 3 spec |
| One-page intro — read this first when starting an integration |
Every entry is also exposed as an MCP resource at
prosodyai://<section>/<id> for clients that prefer resources over tools.
Recipes that ship
recipes/sdk-typescript-quickstart— Add ProsodyAI to a Node / Next.js / browser apprecipes/livekit-realtime-agent— Real-time voice agent with prosody-driven adaptationrecipes/langchain-agent— Use prosody as a LangChain toolrecipes/browser-streaming— Stream mic audio from the browserrecipes/kpi-flow— Define custom KPIs and close the feedback looprecipes/rest-api-integration— Direct REST integration without an SDK
Running locally
npm install
npm run build # syncs content/ from the monorepo, then compiles
npm run start:stdio # for stdio MCP clients
npm run start:http # http on localhost:3333/mcpnpm run build:content rebuilds content/ from the parent monorepo. It
locates the monorepo via PROSODYAI_REPO_ROOT or by walking up from this
package's directory (works when mounted as packages/mcp-docs in the
parent monorepo).
Use it from AureliaStudio (or any MCP client)
Stdio (local)
Add to your client's mcp.json:
{
"mcpServers": {
"prosodyai-docs": {
"command": "npx",
"args": ["-y", "@prosodyai/mcp-docs"]
}
}
}Or run from a checkout:
{
"mcpServers": {
"prosodyai-docs": {
"command": "node",
"args": ["/abs/path/to/mcp-docs/dist/stdio.js"]
}
}
}HTTP (remote)
Once deployed (see below), point your client at the public URL:
{
"mcpServers": {
"prosodyai-docs": {
"url": "https://prosodyai-docs.vercel.app/mcp"
}
}
}Deployment
The HTTP entrypoint is a plain express app that listens on PORT (default
3333) at path /mcp. It works on any Node host:
Vercel / Cloud Run / Fly / Railway: deploy as a Node service with
npm run buildas the build step andnpm run start:httpas the start command.Docker: see
Dockerfile(single-stage Node 20-slim image).
/healthz returns a JSON heartbeat for container orchestrators.
Updating content
Whenever the parent monorepo's docs, SDK READMEs, or OpenAPI spec change:
cd packages/mcp-docs # or wherever this is mounted
npm run build:content
git add content/ && git commit -m "Sync docs from monorepo"The next deploy serves the new content. (CI on ProsodyAI/prosodyai's master
branch should run this automatically — see .github/workflows/sync.yml if
present.)
License
MIT
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