How do I find my PingCode Client ID and Secret?

Log in to the PingCode Enterprise Backend, navigate to [Credential Management] (凭据管理), and create a new application. Your Client ID and Client Secret will be generated there.

Can I create different types of work items like bugs or stories?

Yes. When using `create_work_item`, you can specify the `type` parameter (e.g., 'task', 'story', 'bug') to ensure the item is correctly categorized in your agile project.

Does this server support wiki documentation?

Yes. You can use `list_wiki_pages` to browse through your documentation repositories and `get_wiki_page` to retrieve the content of specific pages for your AI agent to read.

PingCode MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: PingCode
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect PingCode through the 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 PingCode "
            "(10 tools)."
        ),
    )

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

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 PingCode MCP Server

Empower your AI agent to orchestrate your software development lifecycle with PingCode, the premier agile project management platform for R&D teams. By connecting PingCode to your agent, you transform complex issue tracking, sprint planning, and knowledge management into a natural conversation. Your agent can instantly list your agile projects, create work items, monitor sprint progress, and even retrieve wiki pages without you needing to navigate the complex PingCode dashboard. Whether you are following Scrum or Kanban, your agent acts as a real-time R&D assistant, ensuring your development pipeline is always moving and your documentation is accessible.

Pydantic AI validates every PingCode tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through the 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

Agile Management — List agile projects and get detailed information about your development workspace.
Work Item Control — Create and track tasks, stories, and bugs with full support for descriptions and metadata.
Sprint & Release Tracking — Monitor active sprints and upcoming releases to stay on top of your delivery schedule.
Knowledge Management — Browse wiki repositories and retrieve page content to access project documentation instantly.
Team Overview — List organization teams and members to manage collaboration and assignments effectively.

The PingCode MCP Server exposes 10 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 PingCode to Pydantic AI via MCP

Follow these steps to integrate the PingCode 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 10 tools from PingCode with type-safe schemas

Why Use Pydantic AI with the PingCode MCP Server

Pydantic AI provides unique advantages when paired with PingCode 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 PingCode integration code

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

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

PingCode + Pydantic AI Use Cases

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

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

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

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

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

PingCode MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect PingCode to Pydantic AI via MCP:

create_work_item

Create a work item

get_project

Get project details

get_wiki_page

Get wiki page content

list_members

List organization members

list_projects

List PingCode agile projects

list_releases

List project releases

list_sprints

List project sprints

list_teams

List organization teams

list_wiki_pages

List wiki pages

list_work_items

List work items in a project

Example Prompts for PingCode in Pydantic AI

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

"List all agile projects in my PingCode organization."

"Create a new bug item in project 'Checkout Flow' titled 'Payment timeout on mobile'."

"Retrieve the content of the wiki page 'System Architecture' from repository 'PROJ-DOCS'."

Troubleshooting PingCode MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

PingCode + Pydantic AI FAQ

Common questions about integrating PingCode 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 PingCode MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.