rct.ai MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect rct.ai 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({
"rctai": {
"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 rct.ai, 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 rct.ai MCP Server
Connect your AI agents to rct.ai, the advanced narrative engine for the gaming and metaverse industry. This MCP provides 10 tools to orchestrate autonomous virtual beings using the Morpheus Cloud and the Chaos Box algorithm.
LangChain's ecosystem of 500+ components combines seamlessly with rct.ai through native MCP adapters. Connect 10 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
- NPC Interaction — Send user input to NPCs and receive real-time dialogue and behavioral decisions
- Character Lifecycle — Create, update, and inspect AI character profiles and personalities
- Contextual Sessions — Manage persistent interaction sessions between players and virtual beings
- Narrative Logic — Configure the Chaos Box to balance stochastic randomness and scripted narrative flow
The rct.ai MCP Server exposes 10 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 rct.ai to LangChain via MCP
Follow these steps to integrate the rct.ai 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 10 tools from rct.ai via MCP
Why Use LangChain with the rct.ai MCP Server
LangChain provides unique advantages when paired with rct.ai through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine rct.ai 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 rct.ai queries for multi-turn workflows
rct.ai + LangChain Use Cases
Practical scenarios where LangChain combined with the rct.ai MCP Server delivers measurable value.
RAG with live data: combine rct.ai tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query rct.ai, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain rct.ai tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every rct.ai tool call, measure latency, and optimize your agent's performance
rct.ai MCP Tools for LangChain (10)
These 10 tools become available when you connect rct.ai to LangChain via MCP:
create_character
Create a new AI NPC profile
create_session
Initialize a new interaction session
get_chaos_box_config
Retrieve current Chaos Box logic parameters
get_character
Get detailed configuration of a specific AI character
get_session
Retrieve details about an ongoing interaction session
list_assets
List assets or knowledge bases attached to characters
list_characters
List all AI characters managed in your account
send_inference
Send user input to an AI NPC and get a response
update_chaos_box_config
Update Chaos Box decision logic parameters
update_character
Update an existing AI character configuration
Example Prompts for rct.ai in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with rct.ai immediately.
"Send interaction message 'Who are you?' to NPC character 'char_123'."
"List all AI characters managed in my account."
"Get the current Chaos Box configuration."
Troubleshooting rct.ai MCP Server with LangChain
Common issues when connecting rct.ai to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersrct.ai + LangChain FAQ
Common questions about integrating rct.ai 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 rct.ai 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 rct.ai to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.