How to Use the Capacities MCP in CrewAI
Deploy autonomous crews of AI agents to research, organize, and build your Capacities knowledge base with CrewAI.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Capacities MCP to CrewAI
Create your Vinkius account to connect Capacities 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.
Create an autonomous research crew
Assign one agent the role of 'Researcher.' This agent's job is to use external tools to find information online, then use the `save_weblink` tool to store interesting URLs in Capacities. A second 'Archivist' agent can then follow up. It uses `get_object` to read the saved weblinks and then `add_tag` to categorize them. Your crew builds an organized, searchable library without any human input.
Automate daily briefings for your team
A 'Reporter' agent can be tasked to run every morning. It uses `lookup` to find all items tagged 'priority' or created in the last 24 hours inside your shared Capacities space. After gathering the data, the agent formats a summary in Markdown and uses `save_to_daily_note` to append it to that day's note. Your whole team gets a briefing waiting for them, generated automatically by your CrewAI agent.
Maintain your knowledge base with a CrewAI team
Design a 'Janitor' agent that periodically scans your space using this MCP Server. It can use `get_structures` to understand the valid object types you've defined and look for content that doesn't match. If it finds malformed or untagged data, it can either try to fix it with `add_tag` or create a new task object using `create_object`. That new task object can be assigned to a human for review.
Set up Capacities MCP in CrewAI
Prerequisites
- Python 3.10+ installed
-
crewaipackage (pip install crewai) - Active Vinkius subscription with a valid endpoint token
- 1
Install CrewAI
Run
pip install crewaito install the framework. MCP support is built-in via themcpsparameter. - 2
Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the
mcpslist. 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
Crewwith your agent and tasks. Callcrew.kickoff()— the agent will automatically invoke Capacities tools as needed.
from crewai import Agent, Task, Crew
agent = Agent(
role="Capacities Analyst",
goal="Access and analyze Capacities data via MCP.",
backstory="Expert analyst with direct Capacities access.",
mcps=[
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
],
)
task = Task(
description="List recent Capacities transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) Prerequisites
- Python 3.10+ installed
-
crewai+crewai-toolspackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
pip install crewai crewai-tools. TheMCPServerAdapterhandles lifecycle management and tool conversion. - 2
Connect with MCPServerAdapter
Use
MCPServerAdapteras a context manager withSseServerParameterspointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle. - 3
Assign tools and run
Pass the returned
mcp_toolsto your agent'stoolsparameter. The adapter converts MCP tools to nativeBaseToolobjects compatible with all CrewAI agents.
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="Capacities Analyst",
goal="Access and analyze Capacities data via MCP.",
backstory="Expert analyst with direct Capacities access.",
tools=mcp_tools,
)
task = Task(
description="List recent Capacities transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Capacities. 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 Capacities MCP in CrewAI
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