MonkeyLearn 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 MonkeyLearn 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="monkeylearn_agent",
tools=tools,
system_message=(
"You help users with MonkeyLearn. "
"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 MonkeyLearn MCP Server
Connect your MonkeyLearn account to your AI agent and leverage powerful NLP models for text analysis and data extraction through natural conversation.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use MonkeyLearn 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
- Text Classification — Use pre-trained or custom classifiers for sentiment analysis, topic detection, and intent classification.
- Data Extraction — Automatically pull keywords, entities, and specific data points from raw text strings.
- Model Discovery — List and inspect all classifiers, extractors, and pipelines available in your account.
- Workflow Tracking — Monitor your automated workflows and processing activity in real-time.
- Tag Hierarchy — Access the tag trees used by your models to understand classification structures.
- Deep Inspection — Fetch detailed configuration and metadata for specific models using their unique IDs.
The MonkeyLearn 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 MonkeyLearn to AutoGen via MCP
Follow these steps to integrate the MonkeyLearn 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 MonkeyLearn automatically
Why Use AutoGen with the MonkeyLearn MCP Server
AutoGen provides unique advantages when paired with MonkeyLearn through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use MonkeyLearn tools to solve complex tasks
Role-based architecture lets you assign MonkeyLearn 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 MonkeyLearn tool calls
Code execution sandbox: AutoGen agents can write and run code that processes MonkeyLearn tool responses in an isolated environment
MonkeyLearn + AutoGen Use Cases
Practical scenarios where AutoGen combined with the MonkeyLearn MCP Server delivers measurable value.
Collaborative analysis: one agent queries MonkeyLearn while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from MonkeyLearn, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using MonkeyLearn data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process MonkeyLearn responses in a sandboxed execution environment
MonkeyLearn MCP Tools for AutoGen (10)
These 10 tools become available when you connect MonkeyLearn to AutoGen via MCP:
classify_text
Classify text using a model
extract_text
Extract data from text
get_classifier_details
Get classifier metadata
get_extractor_details
Get extractor metadata
list_activity
List account activity
list_classifiers
g., sentiment analysis, topic detection) available in your account. List available classifiers
list_extractors
g., keyword extraction, entity recognition) available in your account. List available extractors
list_pipelines
List MonkeyLearn pipelines
list_tag_trees
List available tag trees
list_workflows
List automated workflows
Example Prompts for MonkeyLearn in AutoGen
Ready-to-use prompts you can give your AutoGen agent to start working with MonkeyLearn immediately.
"Classify the sentiment of this review: 'The product exceeded all my expectations, truly amazing!' using model cl_oZ9GRg8P."
"List all classifiers available in my account."
"Show me my recent processing activity."
Troubleshooting MonkeyLearn MCP Server with AutoGen
Common issues when connecting MonkeyLearn to AutoGen through the Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"MonkeyLearn + AutoGen FAQ
Common questions about integrating MonkeyLearn 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 MonkeyLearn 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 MonkeyLearn to AutoGen
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.