Replicate MCP Server for LangChain 12 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Replicate 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({
"replicate": {
"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 Replicate, 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 Replicate MCP Server
Connect your conversational assistant directly to the Replicate ecosystem. This integration grants your AI the ability to interact programmatically with a vast library of open-source machine learning models without running them on your local hardware. From orchestrating complex image generations to spinning up specialized language models, you can command AI workflows directly from your chat.
LangChain's ecosystem of 500+ components combines seamlessly with Replicate 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
- Execute Predictions — Command the assistant to execute specific model versions on your behalf (
create_prediction) by supplying a payload of variables. Monitor long-running processes by retrieving outputs and execution status reliably (get_prediction) or cancel them at will (cancel_prediction). - Discover Models — Instruct the AI to intelligently scan the Replicate platform for models matching a specific use case using
search_models. You can also explore trending and categorized models by leveraging thelist_collectionsaction. - Analyze Model Metadata — Whenever you discover a new model, query its precise owner and name (
get_model) to extract the exact schema and parameter requirements necessary for a successful execution. You can also view a log of your own executed tasks (list_predictions).
The Replicate 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 Replicate to LangChain via MCP
Follow these steps to integrate the Replicate 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 Replicate via MCP
Why Use LangChain with the Replicate MCP Server
LangChain provides unique advantages when paired with Replicate through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Replicate 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 Replicate queries for multi-turn workflows
Replicate + LangChain Use Cases
Practical scenarios where LangChain combined with the Replicate MCP Server delivers measurable value.
RAG with live data: combine Replicate tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Replicate, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Replicate tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Replicate tool call, measure latency, and optimize your agent's performance
Replicate MCP Tools for LangChain (12)
These 12 tools become available when you connect Replicate to LangChain via MCP:
cancel_prediction
Cancels a prediction that is currently running
create_prediction
g., image generation, LLMs). Provide the model version ID and inputs as a JSON object. Starts a new model prediction on Replicate
get_account
Retrieves the authenticated Replicate account details
get_collection
Provide the collection slug (e.g., "text-to-image"). Retrieves a specific collection of models by its slug
get_model
Retrieves details for a specific model
get_prediction
). Retrieves the status and output of a prediction
list_collections
g., "Image-to-Text", "Audio Generation"). Lists curated collections of models
list_deployments
Lists your active model deployments on Replicate
list_hardware
Lists available GPU hardware options for running models
list_models
Lists public models available on Replicate
list_predictions
Lists recent predictions made by the user
search_models
Searches for public models on Replicate
Example Prompts for Replicate in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Replicate immediately.
"List my recent predictions."
"Query Replicate to search for 'TTS' models."
"Cancel the prediction that has the ID `p_abc123`."
Troubleshooting Replicate MCP Server with LangChain
Common issues when connecting Replicate to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersReplicate + LangChain FAQ
Common questions about integrating Replicate 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 Replicate 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 Replicate to LangChain
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.