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 LlamaIndex 10 tools — connect in under 2 minutes

Name: DocsBot
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add DocsBot as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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 llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to DocsBot. "
            "You have 10 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in DocsBot?"
    )
    print(response)

asyncio.run(main())

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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.

LlamaIndex agents combine DocsBot tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

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 LlamaIndex 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 LlamaIndex via MCP

Follow these steps to integrate the DocsBot MCP Server with LlamaIndex.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from DocsBot

Why Use LlamaIndex with the DocsBot MCP Server

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

Data-first architecture: LlamaIndex agents combine DocsBot tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain DocsBot tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query DocsBot, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what DocsBot tools were called, what data was returned, and how it influenced the final answer

DocsBot + LlamaIndex Use Cases

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

Hybrid search: combine DocsBot real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query DocsBot to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying DocsBot for fresh data

Analytical workflows: chain DocsBot queries with LlamaIndex's data connectors to build multi-source analytical reports

DocsBot MCP Tools for LlamaIndex (10)

These 10 tools become available when you connect DocsBot to LlamaIndex 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 LlamaIndex

Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex

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

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

DocsBot + LlamaIndex FAQ

Common questions about integrating DocsBot MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query DocsBot tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.