How do I get a DocsBot API Key?

Log in to your DocsBot account, navigate to the API section in your account settings, and you can generate or retrieve your unique API Key from there.

Can the agent train my bots?

This integration currently focuses on querying bots and auditing sources. Adding new sources or triggering full training cycles should be managed via the DocsBot dashboard.

Which AI models are used?

DocsBot supports various models including GPT-3.5 and GPT-4. The agent will retrieve results based on the specific model configured for your bot in your account.

DocsBot MCP Server for LangChain 10 tools — connect in under 2 minutes

Name: DocsBot
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect DocsBot 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({
        "docsbot": {
            "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 DocsBot, 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 DocsBot MCP Server

Integrate DocsBot, the AI-powered knowledge base platform, directly into your AI workflow. Manage your custom AI bots, track their data sources (URLs, PDFs, documents), monitor indexing status, and query your bots directly using natural language.

LangChain's ecosystem of 500+ components combines seamlessly with DocsBot through native MCP adapters. Connect 10 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

Bot Oversight — List and retrieve detailed configuration and metadata for all the AI bots in your team.
Knowledge Management — Monitor data sources used to train your bots and track their last indexing timestamps.
Bot Interaction — Query your bots directly via the agent to retrieve AI-generated answers based on your knowledge base.
Analytics & Logs — Access technical logs of recent bot interactions, including questions and generated answers.

The DocsBot MCP Server exposes 10 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 DocsBot to LangChain via MCP

Follow these steps to integrate the DocsBot 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 10 tools from DocsBot via MCP

Why Use LangChain with the DocsBot MCP Server

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

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

DocsBot + LangChain Use Cases

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

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

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

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

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

DocsBot MCP Tools for LangChain (10)

These 10 tools become available when you connect DocsBot to LangChain via MCP:

ask_bot_question

Ask a technical question to a specific DocsBot and retrieve an AI-generated answer

get_bot_details

Get detailed settings and information for a specific bot

get_bot_knowledge_summary

Retrieve a high-level summary of the knowledge base size and source count

get_docsbot_account_metadata

Retrieve metadata for the current authenticated user

list_bot_interaction_logs

List recent questions and answers handled by a specific bot

list_bot_knowledge_sources

List all data sources (URL, PDF, etc.) used to train a specific bot

list_docsbot_teams

List all teams you are a member of in DocsBot

list_recently_indexed_bots

Identify bots that have had their knowledge base updated recently (mock logic)

list_team_bots

List all AI bots configured within a specific team

search_bot_sources

Search for specific knowledge sources by name keyword

Example Prompts for DocsBot in LangChain

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

"Ask our 'API Docs Bot': 'How do I authenticate using the SDK?'."

"List all data sources used by our 'Support Bot'."

"Show me the last 5 questions asked to the 'Sales Bot'."

Troubleshooting DocsBot MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

DocsBot + LangChain FAQ

Common questions about integrating DocsBot 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.