How to Use the Watershed Climate MCP in CrewAI

Q: What tasks can I automate with Watershed Climate using CrewAI?

You can build a pipeline where Agent A uploads data (uploaddatarecords), and Agent B runs validateupload to check quality before the final submission.

Q: What can I check with Watershed Climate and CrewAI?

You can list all existing reports using listreports. This provides essential metadata about report types, generation dates, and scope for your autonomous agents.

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Connect Watershed Climate MCP to CrewAI

Create your Vinkius account to connect Watershed Climate 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 Watershed Climate with CrewAI

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Retrieve Report Details

Need a final document? Use `get_report` to access the full details of a specific report, including generated files and disclosure frameworks covered. You must first get the ID using `list_reports`. This is perfect for an agent tasked with compiling mandatory annual submissions.

Manage Carbon Inputs

The core data starts here. Agents use `upload_data_records` to upload activity records—like electricity or shipping usage—into a container. They can also check the list with `list_uploads` first. This ensures all raw inputs are correctly housed before calculation.

Review Emissions Measurements

After calculating emissions, agents use `list_measurements` to review actual carbon footprint values. They can filter these measurements by a specific inventory ID or year. This gives immediate feedback on the calculated CO2e value before final reporting.

Setup guide

Set up Watershed Climate 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 Watershed Climate tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Watershed Climate 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="Watershed Climate Analyst",
        goal="Access and analyze Watershed Climate data via MCP.",
        backstory="Expert analyst with direct Watershed Climate access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Watershed Climate 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 Watershed Climate. 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 Watershed Climate MCP in CrewAI

CrewAI can assign specialized agents to monitor and manage the process. One agent calls `list_inventories` to gather baseline data, while another focuses on reporting.

You can build a pipeline where Agent A uploads data (`upload_data_records`), and Agent B runs `validate_upload` to check quality before the final submission.

When an agent submits a large dataset, it gets a task ID. The process needs monitoring; therefore, agents use `get_task_status` to confirm the submission is complete.

You can list all existing reports using `list_reports`. This provides essential metadata about report types, generation dates, and scope for your autonomous agents.

The server touches structured activity data records, detailing activities that generate emissions (e.g., electricity consumption or business travel).

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