Which version of Ernie Bot should I use for chat?

For high performance and reasoning, use `ernie-4.0-8k`. For faster response times and cost efficiency, `ernie-speed-128k` or `ernie-lite-8k` are excellent choices.

Can I automatically generate embeddings for RAG?

Yes! Use the `get_embeddings` tool with your text input. The agent will retrieve the vector representations from Baidu's embedding models, ready for indexing in your vector database.

How do I use prompt templates from the console?

Use the `list_prompt_templates` tool to find your configured templates. You can then retrieve specific details using `get_prompt_template` to maintain consistency across your AI workflows.

Baidu Qianfan MCP Server for LangChain 6 tools — connect in under 2 minutes

Name: Baidu Qianfan
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 6 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Baidu Qianfan through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

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({
        "baidu-qianfan": {
            "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 Baidu Qianfan, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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* 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 Baidu Qianfan MCP Server

Connect your AI agents to Baidu Qianfan (百度千帆), the enterprise-grade LLM platform. This MCP provides 10 tools to automate interactions with Ernie Bot and other foundation models, including chat completions, vector embeddings, and prompt engineering.

LangChain's ecosystem of 500+ components combines seamlessly with Baidu Qianfan through native MCP adapters. Connect 6 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

Model Interaction — Trigger chat completions with Ernie Bot (Turbo/Speed/4.0) using persistent context
Vector Embeddings — Generate semantic embeddings for text to power RAG and search workflows
Prompt Engineering — Manage and retrieve centralized prompt templates for consistent model outputs
Image Generation — Trigger Text-to-Image tasks using Baidu's advanced diffusion models
Usage Monitoring — Track token consumption and manage model service status programmatically

The Baidu Qianfan MCP Server exposes 6 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 Baidu Qianfan to LangChain via MCP

Follow these steps to integrate the Baidu Qianfan 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 6 tools from Baidu Qianfan via MCP

Why Use LangChain with the Baidu Qianfan MCP Server

LangChain provides unique advantages when paired with Baidu Qianfan through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Baidu Qianfan 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 Baidu Qianfan queries for multi-turn workflows

Baidu Qianfan + LangChain Use Cases

Practical scenarios where LangChain combined with the Baidu Qianfan MCP Server delivers measurable value.

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

Autonomous research agents: LangChain agents query Baidu Qianfan, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Baidu Qianfan tools with web scrapers, databases, and calculators in a single agent run

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

Baidu Qianfan MCP Tools for LangChain (6)

These 6 tools become available when you connect Baidu Qianfan to LangChain via MCP:

chat_completions

Requires model endpoint name. Send a message to a Baidu Qianfan model

get_embeddings

Generate vector embeddings for text

list_datasets

List uploaded datasets

list_models

List available model services

list_train_jobs

List model training jobs

text_to_image

Generate an image from a text prompt

Example Prompts for Baidu Qianfan in LangChain

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

"Chat with Ernie Bot 4.0 and ask 'Write a formal apology letter for a late shipment'."

"Generate embeddings for the text 'The quick brown fox jumps over the lazy dog'."

"List all my prompt templates in Qianfan."

Troubleshooting Baidu Qianfan MCP Server with LangChain

Common issues when connecting Baidu Qianfan to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Baidu Qianfan + LangChain FAQ

Common questions about integrating Baidu Qianfan MCP Server with LangChain.

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.

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.