GlassFrog MCP Server for OpenAI Agents SDK 12 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect GlassFrog through 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="GlassFrog Assistant",
instructions=(
"You help users interact with GlassFrog. "
"You have access to 12 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from GlassFrog"
)
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 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.
The OpenAI Agents SDK auto-discovers all 12 tools from GlassFrog through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries GlassFrog, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
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 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 GlassFrog to OpenAI Agents SDK via MCP
Follow these steps to integrate the GlassFrog 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 12 tools from GlassFrog
Why Use OpenAI Agents SDK with the GlassFrog MCP Server
OpenAI Agents SDK provides unique advantages when paired with GlassFrog 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
GlassFrog + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the GlassFrog MCP Server delivers measurable value.
Automated workflows: build agents that query GlassFrog, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries GlassFrog, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through GlassFrog tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query GlassFrog to resolve tickets, look up records, and update statuses without human intervention
GlassFrog MCP Tools for OpenAI Agents SDK (12)
These 12 tools become available when you connect GlassFrog to OpenAI Agents SDK 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 OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK 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 OpenAI Agents SDK
Common issues when connecting GlassFrog to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
GlassFrog + OpenAI Agents SDK FAQ
Common questions about integrating GlassFrog 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 GlassFrog 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 GlassFrog to OpenAI Agents SDK
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.