How to Use the BookStack (Wiki) MCP in LangChain

Q: How do I trace BookStack (Wiki) tools inside LangChain using LangSmith?

Every call to search or createbook is logged automatically in your LangSmith trace. You can inspect the exact HTML payload sent to createpage and track latency for every wiki API call.

Build LangChain agents that search, write, and organize your BookStack (Wiki) knowledge base through multi-step reasoning.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect BookStack (Wiki) MCP to LangChain

Create your Vinkius account to connect BookStack (Wiki) 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 BookStack (Wiki) with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Automated Wiki Structure Auditing

Your LangChain agent can walk your entire wiki hierarchy using `list_shelves` and `list_books` to find empty spots or outdated info. By mapping the layout first, the agent identifies legacy sections before drilling down into chapters with `list_chapters`. Every single step of this discovery chain appears inside your LangSmith dashboard, showing you exactly why the agent decided to reorganize a shelf.

LangChain Content Migration Pipelines

This MCP Server lets your LangChain pipeline execute `create_page` to move documentation from legacy platforms into your wiki without manual copy-pasting. By executing `create_attachment`, the runner uploads linked files and ties them directly to the newly created wiki pages, keeping your documentation complete without human intervention.

Intelligent Wiki Search and Summarization

Stop guessing where your team hid deployment guides by letting your LangChain agent use `search` to scan your BookStack (Wiki) setup. After retrieving page content with `get_page`, the agent aggregates the data and updates outdated references using `update_page` to keep your team aligned.

Setup guide

Set up BookStack (Wiki) 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 BookStack (Wiki) 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({
    "bookstack-wiki-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 BookStack (Wiki) 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 BookStack. 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 BookStack (Wiki) 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 BookStack (Wiki) MCP in LangChain

Install the MCP adapter, initialize the client with your Vinkius endpoint, and register the tools. Your agent gets instant access to `list_books` and `create_page` through standard tool-calling patterns.

Yes. By passing the tools to your agent, it can make decisions to call `get_page` first, check the content, and then run `update_page` to refresh stale wiki entries.

Yes. The LangChain multi-server MCP client lets you combine this wiki toolset with databases or notification APIs. Your agent can read a page using `get_page` and immediately post a summary to Slack.

Every call to `search` or `create_book` is logged automatically in your LangSmith trace. You can inspect the exact HTML payload sent to `create_page` and track latency for every wiki API call.

Your wiki pages, chapters, and attachments stay secure inside Vinkius's isolated sandbox. We do not store your wiki credentials or page content, passing them directly to your self-hosted BookStack instance over encrypted connections.

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