Feathery MCP Server for OpenAI Agents SDK 11 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Feathery 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="Feathery Assistant",
instructions=(
"You help users interact with Feathery. "
"You have access to 11 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Feathery"
)
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 Feathery MCP Server
Connect your Feathery.io account to any AI agent and take full control of your form automation and user data management through natural conversation.
The OpenAI Agents SDK auto-discovers all 11 tools from Feathery through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries Feathery, another analyzes results, and a third generates reports, all orchestrated through the Vinkius.
What you can do
- User Orchestration — List all users in your environment and fetch detailed profiles including submission history natively
- Submission Intelligence — Retrieve granular field data submitted by specific users across all your automated forms flawlessly
- Session Monitoring — Query current form sessions to understand user progress and friction points in real-time
- Connector Auditing — List API connector logs to verify data synchronization and troubleshoot integration errors synchronously
- Form Management — List all active forms and retrieve structural details and metadata directly from the cloud
- Workflow Tracking — Inspect automated workflows and their execution status to ensure seamless user journeys
- Identity Context — Verify your API token user profile and account information through the agent flawlessly
The Feathery MCP Server exposes 11 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 Feathery to OpenAI Agents SDK via MCP
Follow these steps to integrate the Feathery 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 11 tools from Feathery
Why Use OpenAI Agents SDK with the Feathery MCP Server
OpenAI Agents SDK provides unique advantages when paired with Feathery 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
Feathery + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Feathery MCP Server delivers measurable value.
Automated workflows: build agents that query Feathery, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents — one queries Feathery, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Feathery tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Feathery to resolve tickets, look up records, and update statuses without human intervention
Feathery MCP Tools for OpenAI Agents SDK (11)
These 11 tools become available when you connect Feathery to OpenAI Agents SDK via MCP:
get_account_info
Get Feathery account details
get_form_details
Get details for a specific form
get_form_session
Retrieve the current state/session of a specific form for a user
get_me
Get current API token identity info
get_user_data
Get all field values submitted by a specific user across forms
get_workflow_details
Get details for a specific workflow
list_connector_logs
List recent API connector error logs for a specific form
list_environments
List available Feathery environments
list_forms
List all forms in your Feathery account
list_users
List all users in your Feathery environment
list_workflows
List all automated workflows
Example Prompts for Feathery in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Feathery immediately.
"List all active forms in my account."
"Show me the data submitted by user user_99."
"Check if there are any connector errors for the Onboarding form."
Troubleshooting Feathery MCP Server with OpenAI Agents SDK
Common issues when connecting Feathery to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Feathery + OpenAI Agents SDK FAQ
Common questions about integrating Feathery 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 Feathery 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 Feathery to OpenAI Agents SDK
Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.
