How to Use the Common Paper MCP in CrewAI
Deploy a crew of specialized agents to manage your Common Paper contracts in CrewAI.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Common Paper MCP to CrewAI
Create your Vinkius account to connect Common Paper 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.
Coordinate multi-agent legal operations with CrewAI
The Common Paper MCP Server provides the tools your CrewAI agents need to divide and conquer contract management. One specialized agent can search for templates using `list_templates` while another drafts the agreements. This division of labor prevents context bloat. By assigning specific tools to specific roles, your crew handles high-volume document workflows without mixing up recipient details or contract terms.
Automate contract follow-ups using specialized agents
The `search_agreements_by_email` tool lets your monitoring agent locate outstanding documents for specific clients. When a contract is stuck, the agent identifies the bottleneck and hands the task to a writer agent to draft a follow-up. If the client needs a new version, the crew uses `send_agreement` to dispatch an updated draft. This keeps your sales pipeline moving without requiring manual tracking from your account executives.
Verify execution status across your entire pipeline
The `list_signed_agreements` tool serves as the final gatekeeper for your autonomous operations crew. A moderator agent runs this check to verify that signatures are complete before signaling the fulfillment crew to start work. If any discrepancies arise, the agent queries `get_agreement` to pull the exact timestamp and signer details. This ensures your automated delivery systems never trigger on unexecuted contracts checked via MCP.
Set up Common Paper 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 Common Paper tools as needed.
from crewai import Agent, Task, Crew
agent = Agent(
role="Common Paper Analyst",
goal="Access and analyze Common Paper data via MCP.",
backstory="Expert analyst with direct Common Paper access.",
mcps=[
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
],
)
task = Task(
description="List recent Common Paper 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="Common Paper Analyst",
goal="Access and analyze Common Paper data via MCP.",
backstory="Expert analyst with direct Common Paper access.",
tools=mcp_tools,
)
task = Task(
description="List recent Common Paper 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 Common Paper. 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 Common Paper MCP in CrewAI
Use it with your favorite AI tools
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