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 LangChain 10 tools — connect in under 2 minutes

Name: PingCode
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect PingCode through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

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 langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "pingcode": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using PingCode, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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Ed25519Audit chain

<40msKill switch

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.

LangChain's ecosystem of 500+ components combines seamlessly with PingCode through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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 LangChain 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 LangChain via MCP

Follow these steps to integrate the PingCode MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 10 tools from PingCode via MCP

Why Use LangChain with the PingCode MCP Server

LangChain provides unique advantages when paired with PingCode through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine PingCode MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across PingCode queries for multi-turn workflows

PingCode + LangChain Use Cases

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

RAG with live data: combine PingCode tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query PingCode, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain PingCode tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every PingCode tool call, measure latency, and optimize your agent's performance

PingCode MCP Tools for LangChain (10)

These 10 tools become available when you connect PingCode to LangChain 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 LangChain

Ready-to-use prompts you can give your LangChain 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 LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

PingCode + LangChain FAQ

Common questions about integrating PingCode MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.