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 CrewAI 10 tools — connect in under 2 minutes

Name: DocsBot
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to DocsBot through Vinkius, pass the Edge URL in the `mcps` parameter and every DocsBot tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="DocsBot Specialist",
    goal="Help users interact with DocsBot effectively",
    backstory=(
        "You are an expert at leveraging DocsBot tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in DocsBot "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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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.

When paired with CrewAI, DocsBot becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call DocsBot tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI via MCP

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

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 10 tools from DocsBot

Why Use CrewAI with the DocsBot MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with DocsBot through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

DocsBot + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries DocsBot for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries DocsBot, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain DocsBot tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries DocsBot against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

DocsBot MCP Tools for CrewAI (10)

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

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

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

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

DocsBot + CrewAI FAQ

Common questions about integrating DocsBot MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.