Can I use this with my self-hosted FastGPT instance?

Yes! Simply provide your custom domain in the **Base URL** field (e.g., `https://fastgpt.mycompany.com`). The MCP will route all requests to your specific instance.

How do I add new data to an existing dataset?

Use the `push_dataset_data` tool. You can send a JSON array of objects containing the text content to be indexed. FastGPT will handle the chunking and embedding automatically.

What is the 'goods_sign' used for in Pinduoduo tools?

Wait, this is the FastGPT FAQ. For FastGPT, you mostly need Dataset IDs and App IDs. The 'goods_sign' is specific to the Pinduoduo MCP. Always check you are using the correct tools for the specific platform.

FastGPT MCP Server for LangChain 12 tools — connect in under 2 minutes

Name: FastGPT
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 12 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect FastGPT 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({
        "fastgpt": {
            "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 FastGPT, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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 FastGPT MCP Server

Connect your AI workflows to FastGPT, the powerful open-source platform for building knowledge-based AI applications. This MCP provides 12 tools for full lifecycle management of datasets, apps, and RAG (Retrieval-Augmented Generation) pipelines.

LangChain's ecosystem of 500+ components combines seamlessly with FastGPT 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

Dataset Orchestration — Create, list, and manage knowledge base datasets with granular control over configurations
Document Ingestion — Push text content or chunks directly to datasets for automatic indexing and vectorization
Semantic Search — Run advanced semantic queries against your knowledge bases to test relevance and RAG quality
Application Management — List and inspect AI applications to monitor their configurations and linked datasets
OpenAI-Compatible Chat — Trigger RAG-powered chat completions with full context, session tracking, and intermediate step visibility

The FastGPT 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 FastGPT to LangChain via MCP

Follow these steps to integrate the FastGPT 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 FastGPT via MCP

Why Use LangChain with the FastGPT MCP Server

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

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

FastGPT + LangChain Use Cases

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

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

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

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

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

FastGPT MCP Tools for LangChain (12)

These 12 tools become available when you connect FastGPT to LangChain via MCP:

chat_completions

Supports chatId for context tracking, streaming, and detailed intermediate steps. Send a message to a FastGPT application

create_dataset

Create a new dataset (knowledge base)

delete_dataset_data

Delete specific data from a dataset

get_app_detail

Get details for a specific AI application

get_dataset_detail

Get details for a specific dataset

get_embeddings

Useful for semantic search outside of FastGPT. Generate text embeddings

list_apps

List AI applications

list_dataset_data

List data items in a dataset

list_datasets

Can filter by parentId or search keyword. List knowledge base datasets

push_dataset_data

Add or update data in a dataset

search_dataset_data

Perform semantic search on a dataset

update_dataset_data

Update existing data in a dataset

Example Prompts for FastGPT in LangChain

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

"List all my AI applications in FastGPT."

"Search dataset 'ds_123' for 'company refund policy'."

"Create a new dataset named 'Internal Documentation'."

Troubleshooting FastGPT MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

FastGPT + LangChain FAQ

Common questions about integrating FastGPT 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.