How to Use the AI21 Labs MCP in LangChain

Q: Can I trace AI21 Labs tool execution times inside LangSmith?

Yes, every call to tools like ai21summarizetext is traced automatically. You'll see the exact payload, execution latency, and token counts directly in your LangChain telemetry.

Q: How does LangChain handle document uploads with AI21 Labs?

Your LangChain agent uses ai21listfiles to find active documents, then feeds the file IDs to ai21contextualanswers. This lets the chain query specific uploaded files dynamically.

Run multi-step LangChain pipelines that fix grammar, summarize documents, and chat using AI21 Labs models.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect AI21 Labs MCP to LangChain

Create your Vinkius account to connect AI21 Labs to LangChain and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup AI21 Labs with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Chain AI21 Labs text processing in LangChain

Your LangChain agents can now feed raw text into `ai21_segment_text` to break down messy documents by topic before processing. The output flows directly into `ai21_summarize_text` to extract clean summaries without leaving your execution chain. This setup uses the MCP Server to let LangGraph agents decide when a document needs structure. If the topic segmentation fails, the agent routes the text to `ai21_grammar_correction` first to clean up the input before attempting another summary.

Context-aware Q&A with LangSmith tracing

Debugging RAG pipelines gets simple when you wire `ai21_contextual_answers` into your LangChain runs. You can watch the exact context payload pass through the MCP tool call right inside your LangSmith dashboard to inspect latencies. When your chain needs to verify facts against a specific document, it calls `ai21_get_file` to fetch the metadata. LangChain tracks these tool transitions natively so you know exactly why an agent chose a specific file.

Automated copy editing pipelines

Build self-correcting writing loops by combining `ai21_paraphrase_text` and `ai21_text_improvements` in a single LangChain runnable. The agent analyzes the style suggestions and automatically rewrites the draft until it meets your tone requirements. Instead of manual copy-editing, this pipeline uses the MCP Server to run grammar checks on the fly. You get clean, styled text output ready for production without writing custom regex or parsing logic.

Setup guide

Set up AI21 Labs MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes AI21 Labs tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "ai21-labs-mcp": {
        "transport": "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,
    )
    result = await agent.ainvoke({
        "messages": "List recent AI21 Labs transactions"
    })
    print(result["messages"][-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by AI21 Labs. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect AI21 Labs now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about AI21 Labs MCP in LangChain

Use the LangChain MCP adapter to map your chain variables directly to `ai21_chat_completion`. The adapter handles the schema mapping so your agent can call the model mid-run.

Yes, every call to tools like `ai21_summarize_text` is traced automatically. You'll see the exact payload, execution latency, and token counts directly in your LangChain telemetry.

Your LangChain agent uses `ai21_list_files` to find active documents, then feeds the file IDs to `ai21_contextual_answers`. This lets the chain query specific uploaded files dynamically.

Yes, you can pull raw data from a database tool in LangChain and pipe it directly to `ai21_grammar_correction` using standard routing.

Your raw text files and prompt inputs are processed within Vinkius's secure, isolated V8 sandboxes. The files you manage via `ai21_delete_file` are deleted permanently from the storage endpoint, ensuring no residual data remains in the execution environment.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript