How to Use the Indiegogo Crowdfunding API MCP in Google ADK

Q: Can I filter campaign searches via Indiegogo Crowdfunding API in Google ADK?

Yes, you use searchindiegogocampaigns to define your filter criteria. The API returns a list of matching projects, which your agent can then iterate over.

Connect the Indiegogo Crowdfunding API to your Google ADK agent. Build data-driven market models on Google Cloud infrastructure.

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Connect Indiegogo Crowdfunding API MCP to Google ADK

Create your Vinkius account to connect Indiegogo Crowdfunding API to Google ADK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Indiegogo Crowdfunding API with Google ADK

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Monitor status with Google ADK

Verify endpoint availability using `check_api_status` to ensure your Google Cloud agents aren't wasting compute cycles on a dead connection. It acts as a circuit breaker for your automated workflows. If the service is down, your agent stops and waits instead of failing mid-task.

Fetch campaign details automatically

Call `get_campaign_details` to feed current project data into your Gemini-powered agent. It parses the details and maps them to your existing BigQuery tables. This setup removes the manual labor of cleaning API responses. Your agent processes the data in its native format, ready for your analysis models.

Taxonomy mapping for your agent

Use `list_indiegogo_categories` to define search boundaries for your agent. It ensures your queries hit the right segments on the platform. Combine this with `search_indiegogo_campaigns` to gather targeted lists of projects. Your agent maintains a clear view of the market without cluttering your logic.

Setup guide

Set up Indiegogo Crowdfunding API MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Indiegogo Crowdfunding API tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Indiegogo Crowdfunding API_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Indiegogo Crowdfunding API tools via MCP.",
    tools=mcp_tools,
)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Indiegogo. 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.

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Common questions about Indiegogo Crowdfunding API MCP in Google ADK

The toolset exposes the API functions directly to your agent. You simply call the functions as if they were local methods. It bridges the gap between your agent and the platform data.

Yes, you use `search_indiegogo_campaigns` to define your filter criteria. The API returns a list of matching projects, which your agent can then iterate over.

The server runs as an MCP instance that your agent connects to via HTTP. It fits right into your existing agent architecture. You don't need to change your cloud deployment to make it work.

The server returns a standard error message. You should implement a retry mechanism or client-side caching to respect platform limits.

It only retrieves public crowdfunding metadata like campaign titles, funding amounts, and category tags. No private user data or payment information is ever accessed or stored.

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