How do I query my chatbot via AI agent?

Use the `send_query` tool with the bot ID and your message. The chatbot responds based on its trained knowledge base.

Can I manage knowledge sources programmatically?

Yes. Use `add_source` to add new URLs, `list_sources` to browse, and `delete_source` to remove outdated sources from any chatbot.

How do I review chat conversations?

Use `list_conversations` to see all chats for a bot, then `get_conversation` to read the full message history of any specific session.

INSTANT PLUG AND PLAY

ThinkStack MCP Server for CrewAIGive CrewAI instant access to 10 tools to Add Source, Check Thinkstack Status, Delete Source, and more

Name: ThinkStack
Availability: InStock
Author: Vinkius

Built by Vinkius GDPR 10 Tools Framework

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

Use with Your AI Agent

Ask AI about this App Connector for CrewAI

Open in ChatGPT Open in Claude Open in Perplexity

The ThinkStack app connector for CrewAI is a standout in the Productivity category — giving your AI agent 10 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="ThinkStack Specialist",
    goal="Help users interact with ThinkStack effectively",
    backstory=(
        "You are an expert at leveraging ThinkStack 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 ThinkStack "
        "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)

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 ThinkStack MCP Server

Connect your ThinkStack account to any AI agent and manage your chatbots, knowledge bases, and conversations through natural language.

When paired with CrewAI, ThinkStack becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call ThinkStack 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

Chatbot Management u2014 List and configure all AI chatbots in your account
Knowledge Base u2014 Add, list, and remove knowledge sources (URLs, documents) for any chatbot
Live Queries u2014 Send messages to your chatbots and receive AI-generated responses in real time
Conversation History u2014 Review all chat sessions with full message history and user metadata
Actions & Webhooks u2014 View all configured REST API actions for your chatbots

The ThinkStack 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.

All 10 ThinkStack tools available for CrewAI

When CrewAI connects to ThinkStack through Vinkius, your AI agent gets direct access to every tool listed below — spanning thinkstack, chatbot-api, ai-manage, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

add_source

The content will be crawled and indexed automatically. Add a knowledge source

check_thinkstack_status

Verify ThinkStack API connectivity

delete_source

Remove a knowledge source

get_bot

Get chatbot details

get_conversation

Get conversation details

list_actions

List bot actions

list_bots

List all chatbots

list_conversations

List conversations

list_sources

List knowledge sources

send_query

Query a chatbot

Connect ThinkStack to CrewAI via MCP

Follow these steps to wire ThinkStack into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

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 ThinkStack

Why Use CrewAI with the ThinkStack MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with ThinkStack 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

ThinkStack + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries ThinkStack 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 ThinkStack, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain ThinkStack 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 ThinkStack against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for ThinkStack in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with ThinkStack immediately.

"List all my chatbots in ThinkStack."

"Ask my Support Bot: 'How do I reset my password?'"

"Add docs.example.com as a knowledge source for my Sales bot."

Troubleshooting ThinkStack MCP Server with CrewAI

Common issues when connecting ThinkStack 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.

ThinkStack + CrewAI FAQ

Common questions about integrating ThinkStack 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.