@avala-ai/mcp-server
OfficialThis server has a remotely hosted endpoint. Open its connector listing for connection details, authentication requirements, and setup instructions:
Avala TypeScript SDK + MCP Server
Official TypeScript SDK and MCP server for the Avala API — the open Physical AI Data Platform. Programmatically manage sensor datasets (MCAP, LiDAR, video), annotation projects, exports, tasks, and fleet devices.
Note: This repository is a read-only mirror. To report bugs or request features, please open an issue. See CONTRIBUTING.md for details.
Packages
Package | Version | Description |
0.5.0 | TypeScript SDK for the Avala API | |
0.5.0 | MCP server for AI assistant integrations |
Related MCP server: Bauplan MCP Server
SDK Quick Start
npm install @avala-ai/sdkimport Avala from "@avala-ai/sdk";
const avala = new Avala(); // reads AVALA_API_KEY env var
// List datasets
const page = await avala.datasets.list({ limit: 10 });
page.items.forEach(d => console.log(d.uid, d.name));
// Get a specific dataset
const dataset = await avala.datasets.get("dataset-uid");
// Create an export
const exp = await avala.exports.create({ project: "project-uid" });
console.log(exp.uid, exp.status);
// List tasks with filters
const tasks = await avala.tasks.list({ project: "project-uid", status: "completed" });Authentication
The client reads your API key from the AVALA_API_KEY environment variable by default:
export AVALA_API_KEY="avk_your_api_key"Or pass it explicitly:
const avala = new Avala({ apiKey: "avk_your_api_key" });Delegated services may instead pass an OAuth access token issued specifically for the Avala API:
const avala = new Avala({ accessToken: apiAudienceAccessToken });apiKey and accessToken are mutually exclusive. Do not pass an ID token or a
token issued for another resource (for example, an MCP-server token); exchange
it for an Avala API-audience token first.
Pagination
All .list() methods return a CursorPage with .items, .hasMore, and .nextCursor:
let page = await avala.datasets.list({ limit: 20 });
for (const dataset of page.items) {
console.log(dataset.name);
}
if (page.hasMore) {
const nextPage = await avala.datasets.list({ cursor: page.nextCursor });
}Error Handling
import Avala, { AvalaError, NotFoundError, RateLimitError } from "@avala-ai/sdk";
try {
const dataset = await avala.datasets.get("nonexistent");
} catch (e) {
if (e instanceof NotFoundError) {
console.log("Dataset not found");
} else if (e instanceof RateLimitError) {
console.log("Rate limited");
} else if (e instanceof AvalaError) {
console.log(`API error: ${e.message}`);
}
}Available Resources
Resource | Methods | Description |
|
| Discover the current credential's scopes, capabilities, and toolsets |
|
| Browse and inspect datasets |
|
| Browse and inspect projects |
|
| Create and manage annotation exports |
|
| Browse tasks with project/status filters |
|
| Manage cloud storage connections |
MCP Server
The @avala-ai/mcp-server package provides an MCP server that lets AI assistants (Claude, etc.) interact with your Avala data.
npm install -g @avala-ai/mcp-server
avala-mcp-serverSee MCP Setup Guide for configuration details.
Development
This is a Bun workspace. To get started (Node 20+ and npm are also required):
bun install --frozen-lockfile
bun run build
bun run test
bun run lintbun run test includes bun run test:package: build both packages, pack them
with npm, install the tarballs into a disposable directory outside the workspace,
and initialize/list tools through the installed MCP executable using Node.
This needs access to the public npm registry for third-party dependencies, but
uses no real Avala credentials and makes no Avala API calls. The SDK and MCP
versions and the MCP server's exact SDK dependency must match; npm does not
rewrite workspace:* when packing.
Documentation
License
MIT - see LICENSE for details.
This server cannot be deployed
Maintenance
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