Feathery MCP Server for AutoGen 11 tools — connect in under 2 minutes
Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Feathery as an MCP tool provider through the Vinkius and every agent in the group can access live data and take action.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
async with McpWorkbench(
server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
transport="streamable_http",
) as workbench:
tools = await workbench.list_tools()
agent = AssistantAgent(
name="feathery_agent",
tools=tools,
system_message=(
"You help users with Feathery. "
"11 tools available."
),
)
print(f"Agent ready with {len(tools)} tools")
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.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Feathery tools. Connect 11 tools through the Vinkius and assign role-based access — a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.
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 AutoGen 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 AutoGen via MCP
Follow these steps to integrate the Feathery MCP Server with AutoGen.
Install AutoGen
Run pip install "autogen-ext[mcp]"
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Integrate into workflow
Use the agent in your AutoGen multi-agent orchestration
Explore tools
The workbench discovers 11 tools from Feathery automatically
Why Use AutoGen with the Feathery MCP Server
AutoGen provides unique advantages when paired with Feathery through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Feathery tools to solve complex tasks
Role-based architecture lets you assign Feathery tool access to specific agents — a data analyst queries while a reviewer validates
Human-in-the-loop support: agents can pause for human approval before executing sensitive Feathery tool calls
Code execution sandbox: AutoGen agents can write and run code that processes Feathery tool responses in an isolated environment
Feathery + AutoGen Use Cases
Practical scenarios where AutoGen combined with the Feathery MCP Server delivers measurable value.
Collaborative analysis: one agent queries Feathery while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from Feathery, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using Feathery data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process Feathery responses in a sandboxed execution environment
Feathery MCP Tools for AutoGen (11)
These 11 tools become available when you connect Feathery to AutoGen 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 AutoGen
Ready-to-use prompts you can give your AutoGen 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 AutoGen
Common issues when connecting Feathery to AutoGen through the Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"Feathery + AutoGen FAQ
Common questions about integrating Feathery MCP Server with AutoGen.
How does AutoGen connect to MCP servers?
Can different agents have different MCP tool access?
Does AutoGen support human approval for tool calls?
Connect Feathery with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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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 AutoGen
Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.
