GlassFrog MCP Server for AutoGen 12 tools — connect in under 2 minutes
Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add GlassFrog 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="glassfrog_agent",
tools=tools,
system_message=(
"You help users with GlassFrog. "
"12 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 GlassFrog MCP Server
Connect your GlassFrog organization to any AI agent to automate your Holacracy governance and tactical operations through the Model Context Protocol (MCP). GlassFrog is the premier platform for self-management and organizational clarity. This MCP server enables you to retrieve circle structures, role definitions, project lists, and performance metrics directly through natural conversation.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use GlassFrog tools. Connect 12 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.
Key Features
- Organizational Oversight — List all circles and role definitions, retrieving detailed purposes and accountabilities for every role in the organization.
- Tactical Project Management — Access and list tactical projects, and programmatically create new projects within specific circles from your chat interface.
- Governance Transparency — Retrieve circle policies and governance records to understand the rules and constraints of your organization.
- Performance Metrics — Access defined metrics and checklist items to track organizational health and tactical progress.
- Workforce Collaboration — List all organization members and search for specific people by email to verify role assignments.
- Real-time Synchronization — Keep your Holacracy data accessible to your AI assistant without leaving your primary workspace.
The GlassFrog MCP Server exposes 12 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 GlassFrog to AutoGen via MCP
Follow these steps to integrate the GlassFrog 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 12 tools from GlassFrog automatically
Why Use AutoGen with the GlassFrog MCP Server
AutoGen provides unique advantages when paired with GlassFrog through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use GlassFrog tools to solve complex tasks
Role-based architecture lets you assign GlassFrog 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 GlassFrog tool calls
Code execution sandbox: AutoGen agents can write and run code that processes GlassFrog tool responses in an isolated environment
GlassFrog + AutoGen Use Cases
Practical scenarios where AutoGen combined with the GlassFrog MCP Server delivers measurable value.
Collaborative analysis: one agent queries GlassFrog while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from GlassFrog, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using GlassFrog data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process GlassFrog responses in a sandboxed execution environment
GlassFrog MCP Tools for AutoGen (12)
These 12 tools become available when you connect GlassFrog to AutoGen via MCP:
create_new_project
Add a project
find_member_by_email
Search member
get_circle_summary
Get circle overview
list_checklist_items
List checklists
list_circle_metrics
List metrics
list_circle_policies
List policies
list_holacracy_circles
List all circles
list_holacracy_roles
List role definitions
list_org_members
List people
list_role_assignments
List assignments
list_tactical_projects
List all projects
verify_api_connection
Check connection
Example Prompts for GlassFrog in AutoGen
Ready-to-use prompts you can give your AutoGen agent to start working with GlassFrog immediately.
"List all active circles in my organization."
"What are the accountabilities for the 'Product Manager' role?"
"Show me the current tactical metrics for the 'Marketing' circle (ID: 123)."
Troubleshooting GlassFrog MCP Server with AutoGen
Common issues when connecting GlassFrog to AutoGen through the Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"GlassFrog + AutoGen FAQ
Common questions about integrating GlassFrog 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 GlassFrog with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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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 GlassFrog to AutoGen
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.