DingTalk MCP Server for OpenAI Agents SDK 10 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect DingTalk through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MCPServerStreamableHttp(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as mcp_server:
agent = Agent(
name="DingTalk Assistant",
instructions=(
"You help users interact with DingTalk. "
"You have access to 10 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from DingTalk"
)
print(result.final_output)
asyncio.run(main())
* 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 DingTalk MCP Server
Connect your DingTalk (钉钉) enterprise account to any AI agent and transform your office operations through natural conversation. DingTalk is Alibaba's comprehensive B2B communication and collaboration platform used by millions of organizations for messaging, attendance tracking, approval workflows, and organizational management.
The OpenAI Agents SDK auto-discovers all 10 tools from DingTalk through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries DingTalk, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
What you can do
- User Management — Query employee profiles, search users by department, and retrieve contact details instantly
- Department Exploration — Navigate organizational hierarchy, list departments and sub-departments, understand reporting structures
- Work Notifications — Send text and markdown formatted messages to employees with rich formatting and clickable links
- Attendance Tracking — Retrieve check-in/check-out records, verify timesheet data, monitor late arrivals and early departures
- Approval Workflows — Create new approval instances (leave requests, reimbursements, purchases) and track their progress
- Approval Status — Query approval process history, identify bottlenecks, and review decision chains
- Markdown Reports — Send beautifully formatted markdown reports, alerts, and summaries to team members
The DingTalk MCP Server exposes 10 tools through the Vinkius. Connect it to OpenAI Agents SDK 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 DingTalk to OpenAI Agents SDK via MCP
Follow these steps to integrate the DingTalk MCP Server with OpenAI Agents SDK.
Install the SDK
Run pip install openai-agents in your Python environment
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Run the script
Save the code above and run it: python agent.py
Explore tools
The agent will automatically discover 10 tools from DingTalk
Why Use OpenAI Agents SDK with the DingTalk MCP Server
OpenAI Agents SDK provides unique advantages when paired with DingTalk through the Model Context Protocol.
Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety
Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure
Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate
First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output
DingTalk + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the DingTalk MCP Server delivers measurable value.
Automated workflows: build agents that query DingTalk, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries DingTalk, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through DingTalk tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query DingTalk to resolve tickets, look up records, and update statuses without human intervention
DingTalk MCP Tools for OpenAI Agents SDK (10)
These 10 tools become available when you connect DingTalk to OpenAI Agents SDK via MCP:
create_approval_process
g., leave request, reimbursement, purchase order) by creating a new approval instance. Requires the approval template code (process_code) from your DingTalk admin, form component values matching the template structure, and the originator's user ID. Returns the process instance ID for tracking. Use this to automate approval workflows directly from AI conversations. Create a new approval workflow instance in DingTalk
get_approval_instance
Returns whether the approval is pending, approved, rejected, or cancelled, along with all reviewer actions and timestamps. Use the process instance ID obtained when creating the approval or from the approval list. Critical for tracking approval progress and understanding bottlenecks. Get status and details of an approval process instance
get_attendance_records
Returns timestamps, checkout types (上班签到/下班签退), location data, and whether the attendance was normal or abnormal (late/early leave). Essential for HR teams to monitor attendance patterns, verify timesheet data, or investigate attendance discrepancies. Date format: YYYY-MM-DD. Get employee attendance/checkout records from DingTalk
get_department_info
Use this to understand organizational hierarchy, identify department leaders, or map the reporting structure before making decisions about notification routing. Get detailed information about a DingTalk department
get_user_info
Use the user ID (userid) which can be obtained from the department user list. Essential for looking up employee details before sending targeted notifications or checking organizational structure. Get DingTalk user profile information by user ID
list_all_departments
This is the fastest way to understand the organizational structure, identify department IDs for further queries, and map team hierarchies. Use this before querying users or sub-departments to identify the correct department IDs. List all top-level departments in the DingTalk organization
list_sub_departments
Essential for exploring organizational structure, identifying team subdivisions, or mapping the complete departmental hierarchy. Start with department_id 1 to list all top-level departments in your organization. List all sub-departments under a parent department
list_users_by_department
Returns user IDs, names, avatars, and basic profile information. Useful for identifying team members before sending group notifications, checking team composition, or understanding departmental structure. Use department ID 1 for the root company directory. List all users in a specific DingTalk department
send_markdown_message
Ideal for sending structured reports, formatted alerts, or detailed notifications with clickable links. The title appears as the notification header, while the text body supports full markdown syntax including **bold**, *italic*, [hyperlinks](url), and line breaks. User IDs should be comma-separated. Send a rich formatted markdown message to DingTalk users
send_work_notification
Supports text and markdown message types. The message appears in the recipient's DingTalk work notification feed. User IDs should be comma-separated for multiple recipients. This is ideal for sending alerts, reminders, task assignments, or status updates to team members directly through DingTalk. Send a work notification message to DingTalk users
Example Prompts for DingTalk in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with DingTalk immediately.
"List all users in department ID 12345."
"Send a markdown notification to user1,user2 with title 'Sprint Review' and content about tomorrow's meeting at 2pm."
"Check attendance records for user1,user2 from 2024-01-15 to 2024-01-19."
Troubleshooting DingTalk MCP Server with OpenAI Agents SDK
Common issues when connecting DingTalk to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
DingTalk + OpenAI Agents SDK FAQ
Common questions about integrating DingTalk MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
Connect DingTalk with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect DingTalk to OpenAI Agents SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.