GlassFrog MCP Server for LangChain 12 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect GlassFrog through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MultiServerMCPClient({
"glassfrog": {
"transport": "streamable_http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using GlassFrog, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
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.
LangChain's ecosystem of 500+ components combines seamlessly with GlassFrog through native MCP adapters. Connect 12 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
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 LangChain 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 LangChain via MCP
Follow these steps to integrate the GlassFrog MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 12 tools from GlassFrog via MCP
Why Use LangChain with the GlassFrog MCP Server
LangChain provides unique advantages when paired with GlassFrog through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine GlassFrog MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across GlassFrog queries for multi-turn workflows
GlassFrog + LangChain Use Cases
Practical scenarios where LangChain combined with the GlassFrog MCP Server delivers measurable value.
RAG with live data: combine GlassFrog tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query GlassFrog, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain GlassFrog tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every GlassFrog tool call, measure latency, and optimize your agent's performance
GlassFrog MCP Tools for LangChain (12)
These 12 tools become available when you connect GlassFrog to LangChain 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 LangChain
Ready-to-use prompts you can give your LangChain 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 LangChain
Common issues when connecting GlassFrog to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersGlassFrog + LangChain FAQ
Common questions about integrating GlassFrog MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
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 LangChain
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.