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 CrewAI 10 tools — connect in under 2 minutes

Name: PingCode
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to PingCode through the Vinkius — pass the Edge URL in the `mcps` parameter and every PingCode tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="PingCode Specialist",
    goal="Help users interact with PingCode effectively",
    backstory=(
        "You are an expert at leveraging PingCode tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token — get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in PingCode "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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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.

When paired with CrewAI, PingCode becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call PingCode tools autonomously — one agent queries data, another analyzes results, a third compiles reports — all orchestrated through the Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI via MCP

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

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py — CrewAI auto-discovers 10 tools from PingCode

Why Use CrewAI with the PingCode MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with PingCode through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles — one agent researches, another analyzes, a third generates reports — each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass the Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

PingCode + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries PingCode for raw data, then a second analyst agent cross-references findings and flags anomalies — all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries PingCode, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain PingCode tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries PingCode against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

PingCode MCP Tools for CrewAI (10)

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

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

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

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts — check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

The Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

PingCode + CrewAI FAQ

Common questions about integrating PingCode MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily — when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.