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Mod.io MCP Server for LangChainGive LangChain instant access to 22 tools to Add Collection, Add Mod, Delete Mod, and more

MCP Inspector GDPR Free for Subscribers

LangChain is the leading Python framework for composable LLM applications. Connect Mod.io 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 for LangChain

The Mod.io MCP Server for LangChain is a standout in the Developer Tools category — giving your AI agent 22 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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python
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({
        "modio": {
            "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 Mod.io, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())
Mod.io
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Mod.io MCP Server

Connect your mod.io account to any AI agent to manage your gaming library and modding workflows through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Mod.io through native MCP adapters. Connect 22 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

  • Game Discovery — Browse all games on the platform using get_games and fetch detailed stats and metadata for specific titles with get_game_stats.
  • Mod Management — Search for mods using get_mods, view detailed descriptions with get_mod, and manage your own mod profiles including adding, editing, or deleting entries.
  • User Subscriptions — Subscribe or unsubscribe from mods using subscribe_mod and unsubscribe_mod, rate content with rate_mod, and track your personal collections.
  • Account Insights — Access your profile with get_me, check your wallet information via get_wallets, and view purchased content directly through the API.

The Mod.io MCP Server exposes 22 tools through the Vinkius. Connect it to LangChain in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 22 Mod.io tools available for LangChain

When LangChain connects to Mod.io through Vinkius, your AI agent gets direct access to every tool listed below — spanning modding, user-generated-content, game-api, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

add

Add collection on Mod.io

Requires OAuth 2 Access Token. Create a new mod collection

add

Add mod on Mod.io

Requires OAuth 2 Access Token. Add a new mod to a game

delete

Delete mod on Mod.io

Requires OAuth 2 Access Token. Delete a mod

edit

Edit mod on Mod.io

Requires OAuth 2 Access Token. Edit details of an existing mod

get

Get collection mods on Mod.io

Get mods within a collection

get

Get collections on Mod.io

Get all mod collections for a game

get

Get game on Mod.io

Get details for a specific game

get

Get game stats on Mod.io

Get statistics for a game

get

Get games on Mod.io

io platform. Get all games on mod.io

get

Get me on Mod.io

Requires OAuth 2 Access Token. Get authenticated user details

get

Get mod on Mod.io

Get details for a specific mod

get

Get mod file on Mod.io

Get a specific modfile

get

Get mod files on Mod.io

Get all files for a mod

get

Get mods on Mod.io

Get all mods for a game

get

Get my purchases on Mod.io

Requires OAuth 2 Access Token. Get mods purchased by the user

get

Get my ratings on Mod.io

Requires OAuth 2 Access Token. Get ratings submitted by the user

get

Get my subscriptions on Mod.io

Requires OAuth 2 Access Token. Get mods the user is subscribed to

get

Get my wallets on Mod.io

Requires OAuth 2 Access Token. Get user wallets for monetization

get

Get terms on Mod.io

Get text and links for user consent dialogs

rate

Rate mod on Mod.io

Requires OAuth 2 Access Token. Rate a mod

subscribe

Subscribe mod on Mod.io

Requires OAuth 2 Access Token. Subscribe to a mod

unsubscribe

Unsubscribe mod on Mod.io

Requires OAuth 2 Access Token. Unsubscribe from a mod

Connect Mod.io to LangChain via MCP

Follow these steps to wire Mod.io into LangChain. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

01

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save the code and run python agent.py
04

Explore tools

The agent discovers 22 tools from Mod.io via MCP

Why Use LangChain with the Mod.io MCP Server

LangChain provides unique advantages when paired with Mod.io through the Model Context Protocol.

01

The largest ecosystem of integrations, chains, and agents. combine Mod.io MCP tools with 500+ LangChain components

02

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

03

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

04

Memory and conversation persistence let agents maintain context across Mod.io queries for multi-turn workflows

Mod.io + LangChain Use Cases

Practical scenarios where LangChain combined with the Mod.io MCP Server delivers measurable value.

01

RAG with live data: combine Mod.io tool results with vector store retrievals for answers grounded in both real-time and historical data

02

Autonomous research agents: LangChain agents query Mod.io, synthesize findings, and generate comprehensive research reports

03

Multi-tool orchestration: chain Mod.io tools with web scrapers, databases, and calculators in a single agent run

04

Production monitoring: use LangSmith to trace every Mod.io tool call, measure latency, and optimize your agent's performance

Example Prompts for Mod.io in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Mod.io immediately.

01

"List all games available on mod.io."

02

"Show me the mods for game ID 123."

03

"Rate mod 789 for game 123 as positive."

Troubleshooting Mod.io MCP Server with LangChain

Common issues when connecting Mod.io to LangChain through Vinkius, and how to resolve them.

01

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Mod.io + LangChain FAQ

Common questions about integrating Mod.io MCP Server with LangChain.

01

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.
02

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.
03

Can I trace MCP tool calls in LangSmith?

Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.

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