How to Use the Kitetags MCP in CrewAI

Q: Can a CrewAI researcher agent create tag groups autonomously with Kitetags?

Yes. Your agent can call creategroup whenever it identifies a new high-performing trend category. It can then use createtag to populate that group with high-impact options.

Deploy specialized agent teams to automate your Instagram and TikTok hashtag strategy with CrewAI.

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Connect Kitetags MCP to CrewAI

Create your Vinkius account to connect Kitetags to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Kitetags with CrewAI

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Run multi-agent tag research with CrewAI

The `search_tags` tool gives your research agent immediate access to trending social media hashtags. Instead of a single bot trying to do everything, your CrewAI team splits the workload. One agent finds the raw tags, a second agent runs `get_tag_analytics` to pull reach metrics, and a third agent uses `create_group` to organize them. This collaborative loop runs completely autonomously in the background.

Audit campaign groups autonomously

The `list_groups` tool retrieves all active hashtag categories stored in your system. A dedicated auditor agent runs this tool periodically to keep your marketing campaigns structured and clean. The agent checks each group using `list_group_tags` to identify underperforming tags. If a tag's engagement drops, the agent calls `delete_tag` to prune the group without human intervention.

Optimize social reach using an MCP Server

The `get_tag` tool retrieves deep metadata for individual social media tags. Your optimization agent analyzes this data to compare platform performance across TikTok and Instagram. By feeding these metrics into your crew's shared memory, every agent on the team stays updated on which tags are driving the most impressions. This coordinates your entire posting strategy around high-value targets.

Setup guide

Set up Kitetags MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Kitetags tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Kitetags Analyst",
    goal="Access and analyze Kitetags data via MCP.",
    backstory="Expert analyst with direct Kitetags access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Kitetags transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Kitetags Analyst",
        goal="Access and analyze Kitetags data via MCP.",
        backstory="Expert analyst with direct Kitetags access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Kitetags transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

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

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 Kitetags. 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.

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Common questions about Kitetags MCP in CrewAI

You can pass your Vinkius HTTP URL directly in the agent's array. This MCP integration allows you to use `MCPServerHTTP` to filter which of the 12 tools your agents can access.

Yes. Your agent can call `create_group` whenever it identifies a new high-performing trend category. It can then use `create_tag` to populate that group with high-impact options.

CrewAI uses a shared memory system. When one agent pulls data via `get_tag_analytics`, the results are accessible to all other agents in the crew, preventing duplicate API calls.

The crew handles failures gracefully based on your execution settings. If the MCP server returns a connection issue during `check_kitetags_status`, the manager agent can pause the task or route it to a fallback handler.

All operations involving your hashtag lists, group taxonomies, and trend metrics run inside an ephemeral V8 sandbox on Vinkius. This zero-trust environment ensures your campaign strategies remain completely private and isolated.

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