How to Use the Canny MCP in Google ADK

Q: Can Google ADK filter which Canny MCP tools are exposed?

Yes. You can use the toolnames filter in the toolset configuration. If you only want your agent to read data, restrict it to listfeedbackboards and getpostdetails.

Q: Will Canny work with my existing BigQuery pipelines?

It will. The agent pulls raw JSON from Canny via listfeedbackposts. You can write custom logic to parse that output and insert it directly into your Vertex AI or BigQuery datasets.

Q: Does Google ADK support adding comments to Canny?

It does. The agent invokes the addcomment tool with the post ID and the text payload. It posts exactly what the Gemini model generates.

Give your Google ADK agents direct MCP access to Canny. Read feedback, tally votes, and manage feature requests using Gemini models.

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Setup Canny with Google ADK

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Perplexity

Feed Canny data to Gemini

Gemini thrives on massive context windows. You can pull thousands of feature requests using `list_feedback_posts` and dump them straight into the model prompt. It digests the entire history of your product roadmap in one pass. Enterprise agents need this depth to spot trends. When a user asks about a specific bug, the agent runs `get_post_details` and cross-references that Canny data with your internal BigQuery logs.

Build Google ADK triage agents

Stop manually copying support tickets into your roadmap. Your agent listens to incoming chats and fires `create_feedback_post` the moment it detects a valid feature request. It handles the categorization automatically. Tracking community demand happens in the background. The agent uses `vote_on_post` to attach new upvotes when customers mention existing ideas. This MCP Server turns passive conversations into structured product data.

Audit user engagement metrics

Knowing who asked for a feature changes how you prioritize it. Your agent triggers `list_users` to map Canny accounts to your Google Cloud customer records. It builds a complete picture of who wants what. It goes deeper into specific requests. By calling `list_comments` and `list_votes`, the agent extracts the exact arguments users made for a feature. You get a summarized brief of the debate without reading 50 individual comments.

Setup guide

Set up Canny 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 Canny 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="Canny_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Canny tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Canny MCP in Google ADK

Run pip install google-adk in your environment. Create a McpToolset using StreamableHttpServerParameters with your Vinkius URL, then pass it to the tools list in your LlmAgent.

Yes. You can use the tool_names filter in the toolset configuration. If you only want your agent to read data, restrict it to `list_feedback_boards` and `get_post_details`.

It will. The agent pulls raw JSON from Canny via `list_feedback_posts`. You can write custom logic to parse that output and insert it directly into your Vertex AI or BigQuery datasets.

It does. The agent invokes the `add_comment` tool with the post ID and the text payload. It posts exactly what the Gemini model generates.

Your Canny API tokens never touch the Google Cloud environment. Vinkius handles the authentication via a zero-trust proxy. When your agent executes `get_account_info`, it only receives the specific JSON payload requested.

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