How to Use the CompanyCam MCP in Vercel AI SDK

Q: How does this MCP Server handle large volumes of CompanyCam photos in Vercel AI SDK?

The server uses pagination parameters inside listallphotos to keep payloads small. Your Vercel AI SDK application can request specific chunks of photos to prevent edge function timeouts and keep memory usage low.

Stream construction updates and jobsite photos directly into your Next.js app using the Vercel AI SDK.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect CompanyCam MCP to Vercel AI SDK

Create your Vinkius account to connect CompanyCam to Vercel AI SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup CompanyCam with Vercel AI SDK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Stream CompanyCam Photos with Vercel AI SDK

The `list_all_photos` tool fetches live images from active jobsites across your entire organization. Your AI client uses this MCP Server to retrieve visual updates, which immediately stream into your React frontend without forcing users to wait for a full page reload. Users get instant visual confirmation of project progress. You can use `get_photo_details` alongside it to render metadata like creator ID and timestamps directly next to the image asset.

Instant Project Setup on the Edge

The `create_project` tool lets your agent spin up new jobsites on CompanyCam the second a client signs a contract. Running on Vercel Edge Functions, this setup executes with minimal latency, keeping your database and jobsite records in sync. Users can search for existing folders first using `search_projects` to prevent duplicates. If no match exists, the agent creates the file structure and displays the fresh project dashboard in the UI immediately.

Real-Time Document Delivery via MCP Server

The `list_project_documents` tool pulls PDF contracts, permits, and blueprints from specific jobsites. By exposing this to your LLM, field workers can ask for the latest permit and see the document link render in their chat window instantly. This eliminates manual searching through deep folder hierarchies. Your interface uses `get_project` to verify the location details before serving the files, ensuring crews reference the correct physical site.

Setup guide

Set up CompanyCam MCP in Vercel AI SDK

Prerequisites

Node.js 18+ and a TypeScript project
ai + @modelcontextprotocol/sdk packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies

Run npm install ai @modelcontextprotocol/sdk plus your preferred model provider (e.g. @ai-sdk/openai).
2

Create the Streamable HTTP transport

Use StreamableHTTPClientTransport with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and use tools

Call mcpClient.tools() to auto-discover all CompanyCam tools. Pass them directly to generateText() or streamText() — no manual schema definitions needed.
4

Works with any model provider

Swap openai("gpt-4o") for any AI SDK provider — Anthropic, Google, Mistral. The MCP tools work identically across all supported models.

index.ts

import { experimental_createMCPClient as createMCPClient } from "ai";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

const transport = new StreamableHTTPClientTransport(
  new URL("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
);

const mcpClient = await createMCPClient({ transport });
const tools = await mcpClient.tools();

const { text } = await generateText({
  model: openai("gpt-4o"),
  tools,
  prompt: "List recent CompanyCam transactions",
});

console.log(text);
await mcpClient.close();

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by CompanyCam. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect CompanyCam now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about CompanyCam MCP in Vercel AI SDK

Initialize the MCP client with your Vinkius endpoint URL and pass the tools to `streamText`. You will need to handle authentication via the provided OAuth provider option during client initialization.

Yes, the Vercel AI SDK handles tool outputs as UI elements. When `list_project_photos` runs, the JSON payload streams to the client, allowing your React components to render the images without waiting for the complete LLM response.

The server uses pagination parameters inside `list_all_photos` to keep payloads small. Your Vercel AI SDK application can request specific chunks of photos to prevent edge function timeouts and keep memory usage low.

Currently, this server focuses on creation and retrieval. Your agent can create new locations with `create_project` and search existing ones with `search_projects`, but editing existing metadata requires direct API calls outside this specific toolset.

Your construction photos, documents, and project metadata remain safely inside CompanyCam's servers. Vinkius runs the integration in an ephemeral sandbox, meaning no image data or project files are stored on Vinkius servers after the request completes.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript