Can I add a vote to a post using the agent?

Yes! Use the `vote_on_post` tool with the Post ID and Voter ID. Your agent will add the vote in Canny, helping prioritize the feedback item.

How do I list all the planned features from a specific board?

Simply ask the agent to `list_feedback_posts` and provide the Board ID and set the status to `planned`. It will retrieve all matching posts from your Canny account.

Does the integration allow creating a new feedback post?

Yes. Use the `create_feedback_post` action and provide the Board ID, Author ID, title, and details. The new item will be added to your Canny board instantly.

Canny MCP Server for Pydantic AI 11 tools — connect in under 2 minutes

Name: Canny
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 11 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Canny through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Canny "
            "(11 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Canny?"
    )
    print(result.data)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Canny MCP Server

Connect your Canny account to any AI agent and orchestrate your product feedback, roadmap prioritization, and community engagement through natural conversation.

Pydantic AI validates every Canny tool response against typed schemas, catching data inconsistencies at build time. Connect 11 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Post Oversight — List and retrieve detailed metadata for all feedback items (ideas, feature requests, bugs) across your boards.
Roadmap Coordination — Monitor the status of posts (Planned, In-Progress, Complete) to stay aligned with your product strategy.
Community Engagement — Add votes and comments to posts directly from your workspace to interact with user feedback.
Board Management — List all feedback boards and retrieve their specific configuration and categories.
User Tracking — Access your directory of users who have interacted with your boards to understand your community.
Feedback Creation — Create new posts directly from your workspace with titles, details, and associated authors.

The Canny MCP Server exposes 11 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Canny to Pydantic AI via MCP

Follow these steps to integrate the Canny MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 11 tools from Canny with type-safe schemas

Why Use Pydantic AI with the Canny MCP Server

Pydantic AI provides unique advantages when paired with Canny through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Canny integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Canny connection logic from agent behavior for testable, maintainable code

Canny + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Canny MCP Server delivers measurable value.

Type-safe data pipelines: query Canny with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Canny tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Canny and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Canny responses and write comprehensive agent tests

Canny MCP Tools for Pydantic AI (11)

These 11 tools become available when you connect Canny to Pydantic AI via MCP:

add_comment

Add a comment to a feedback post

create_feedback_post

Create a new feedback post (idea, bug, etc)

get_account_info

Retrieve core account information

get_board_details

Get details of a specific board

get_post_details

Get details of a specific feedback post

list_comments

List comments for a specific feedback post

list_feedback_boards

List all feedback boards

list_feedback_posts

List feedback items (posts) from a specific board

list_users

List users who have interacted with your boards

list_votes

List votes for a specific post

vote_on_post

Add a vote to a feedback post

Example Prompts for Canny in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Canny immediately.

"List all active feedback boards in Canny."

"Show the top 5 most voted posts on the 'Feature Requests' board."

"Add a comment 'Great idea!' to post ID 99283 as author user_123."

Troubleshooting Canny MCP Server with Pydantic AI

Common issues when connecting Canny to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Canny + Pydantic AI FAQ

Common questions about integrating Canny MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Canny MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.