Float MCP Server for LangChain 12 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Float 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({
"float": {
"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 Float, 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 Float MCP Server
Connect your Float account to any AI agent and automate your resource management and team scheduling through the Model Context Protocol (MCP). Float is the leading resource planning platform that helps agencies and teams keep track of who is working on what and when. Now, you can manage allocations, check availability, and oversee project timelines directly through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with Float 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.
What you can do
- Team Scheduling — List all team members and fetch detailed availability and profile metadata.
- Project Oversight — Access active projects, retrieve specific project details, and manage the team members assigned to them.
- Task Allocations — Create and list project allocations, assigning specific hours and dates to team members instantly.
- Time Off Management — Monitor scheduled vacations, sick leave, and public holidays to ensure accurate capacity planning.
- Logged Time Analysis — Retrieve actual hours worked versus scheduled time to track project progress and efficiency.
- Organization Discovery — List clients, departments, and account users to maintain full context of your agency's structure.
- Capacity Planning — Fetch high-level snapshots of team utilization and task labels (e.g., Design, Development).
The Float 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 Float to LangChain via MCP
Follow these steps to integrate the Float 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 Float via MCP
Why Use LangChain with the Float MCP Server
LangChain provides unique advantages when paired with Float through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Float 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 Float queries for multi-turn workflows
Float + LangChain Use Cases
Practical scenarios where LangChain combined with the Float MCP Server delivers measurable value.
RAG with live data: combine Float tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Float, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Float tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Float tool call, measure latency, and optimize your agent's performance
Float MCP Tools for LangChain (12)
These 12 tools become available when you connect Float to LangChain via MCP:
create_allocation
Schedule a task
get_logged_time
Get actual hours
get_person
Get person details
get_project
Get project details
list_allocations
List task allocations
list_clients
List clients
list_departments
List departments
list_people
List team members
list_project_task_names
g. Design, Dev). List task labels
list_projects
List projects
list_time_offs
List time off
list_user_accounts
List user accounts
Example Prompts for Float in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Float immediately.
"List all active projects in Float and the team members assigned to them."
"Schedule John Doe for 4 hours a day on the 'Q3 Marketing' project from Monday to Friday."
"Who is scheduled for time off this month?"
Troubleshooting Float MCP Server with LangChain
Common issues when connecting Float to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersFloat + LangChain FAQ
Common questions about integrating Float 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 Float 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 Float to LangChain
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.