Observe.AI MCP Server for AutoGen 10 tools — connect in under 2 minutes
Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Observe.AI as an MCP tool provider through 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="observeai_agent",
tools=tools,
system_message=(
"You help users with Observe.AI. "
"10 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 Observe.AI MCP Server
Connect your Observe.AI account to your AI agent and gain deep visibility into your contact center performance and conversation intelligence through natural conversation.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Observe.AI tools. Connect 10 tools through 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
- Interaction Monitoring — List and inspect all calls, chats, and emails processed by the platform, including metadata and analysis.
- Full Transcripts — Retrieve the complete text transcripts for any call or chat interaction for detailed review.
- QA & Evaluations — Access quality assurance scores, evaluation forms, and individual agent performance metrics.
- AI Insights — View automated interaction summaries and identified business moments (e.g., Greetings, Objections).
- Coaching Oversight — Monitor agent coaching sessions and feedback logs to track improvement.
- Workspace Management — List all agents, supervisors, and admins in your Observe.AI instance.
The Observe.AI MCP Server exposes 10 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 Observe.AI to AutoGen via MCP
Follow these steps to integrate the Observe.AI 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 10 tools from Observe.AI automatically
Why Use AutoGen with the Observe.AI MCP Server
AutoGen provides unique advantages when paired with Observe.AI through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Observe.AI tools to solve complex tasks
Role-based architecture lets you assign Observe.AI 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 Observe.AI tool calls
Code execution sandbox: AutoGen agents can write and run code that processes Observe.AI tool responses in an isolated environment
Observe.AI + AutoGen Use Cases
Practical scenarios where AutoGen combined with the Observe.AI MCP Server delivers measurable value.
Collaborative analysis: one agent queries Observe.AI while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from Observe.AI, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using Observe.AI data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process Observe.AI responses in a sandboxed execution environment
Observe.AI MCP Tools for AutoGen (10)
These 10 tools become available when you connect Observe.AI to AutoGen via MCP:
get_evaluation_details
Get specific evaluation info
get_interaction_details
Get specific interaction info
get_interaction_transcript
Get interaction transcript
list_coaching_sessions
List agent coaching sessions
list_evaluation_forms
List QA evaluation forms
list_interaction_moments
g. Greeting, Closing) across interactions. List identified key moments
list_interaction_summaries
List AI-generated summaries
list_interactions
AI. List contact center interactions
list_qa_evaluations
List QA evaluations
list_workspace_users
AI workspace. List workspace agents and users
Example Prompts for Observe.AI in AutoGen
Ready-to-use prompts you can give your AutoGen agent to start working with Observe.AI immediately.
"List all recent call interactions from today."
"What is the QA score for interaction ID 'int_12345'?"
"Show me the AI summaries for our latest interactions."
Troubleshooting Observe.AI MCP Server with AutoGen
Common issues when connecting Observe.AI to AutoGen through the Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"Observe.AI + AutoGen FAQ
Common questions about integrating Observe.AI 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 Observe.AI 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 Observe.AI to AutoGen
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.