IBM watsonx 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 IBM watsonx through the 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="IBM watsonx Assistant",
instructions=(
"You help users interact with IBM watsonx. "
"You have access to 10 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from IBM watsonx"
)
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 IBM watsonx MCP Server
Connect IBM watsonx to any AI agent via MCP.
How to Connect IBM watsonx to OpenAI Agents SDK via MCP
Follow these steps to integrate the IBM watsonx 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 IBM watsonx
Why Use OpenAI Agents SDK with the IBM watsonx MCP Server
OpenAI Agents SDK provides unique advantages when paired with IBM watsonx 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
IBM watsonx + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the IBM watsonx MCP Server delivers measurable value.
Automated workflows: build agents that query IBM watsonx, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents — one queries IBM watsonx, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through IBM watsonx tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query IBM watsonx to resolve tickets, look up records, and update statuses without human intervention
IBM watsonx MCP Tools for OpenAI Agents SDK (10)
These 10 tools become available when you connect IBM watsonx to OpenAI Agents SDK via MCP:
create_prompt
Create a new prompt in watsonx
generate_chat
Use this for multi-turn conversational AI applications. Generate chat completions using a watsonx chat model
generate_embeddings
Useful for similarity search, clustering, and semantic analysis. Generate vector embeddings for input texts
generate_text
Use this for single-turn text generation tasks like content creation, summarization, or analysis. Generate text using a watsonx foundation model
get_model_details
Get detailed specifications for a specific foundation model
get_tuning_status
Get the status of a prompt tuning job
list_models
ai, including model IDs, families, capabilities, and lifecycle states. List available foundation models in watsonx
list_projects
List watsonx projects in your account
list_prompts
List saved prompts in the watsonx project
start_model_tuning
Requires a URL pointing to the training data in cloud storage. Start a prompt tuning job for a foundation model
Troubleshooting IBM watsonx MCP Server with OpenAI Agents SDK
Common issues when connecting IBM watsonx to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
IBM watsonx + OpenAI Agents SDK FAQ
Common questions about integrating IBM watsonx 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 IBM watsonx with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
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 IBM watsonx to OpenAI Agents SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.