Watershed Climate MCP Server for CrewAI 16 tools — connect in under 2 minutes
Connect your CrewAI agents to Watershed Climate through the Vinkius — pass the Edge URL in the `mcps` parameter and every Watershed Climate tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
from crewai import Agent, Task, Crew
agent = Agent(
role="Watershed Climate Specialist",
goal="Help users interact with Watershed Climate effectively",
backstory=(
"You are an expert at leveraging Watershed Climate 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 Watershed Climate "
"and summarize their capabilities."
),
agent=agent,
expected_output=(
"A detailed summary of 16 available tools "
"and what they can do."
),
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)
* 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 Watershed Climate MCP Server
Connect your Watershed Climate organization to any AI agent and take full control of your carbon measurement, reporting, and reduction workflows through natural conversation.
When paired with CrewAI, Watershed Climate becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Watershed Climate tools autonomously — one agent queries data, another analyzes results, a third compiles reports — all orchestrated through the Vinkius with zero configuration overhead.
What you can do
- Data Uploads — Create upload containers, add activity data records (electricity, travel, shipping), and validate data quality
- Batch Data Ingestion — Upload multiple activity records in batch with proper formatting and emission factor mapping
- GHG Inventories — List and inspect greenhouse gas inventories with Scope 1, 2, and 3 emissions breakdowns
- Emissions Measurements — Query calculated carbon footprint measurements filtered by inventory or year
- Processing Tasks — Monitor async processing tasks from upload submissions with real-time status checks
- Reports & Disclosures — List and access generated sustainability reports (CDP, TCFD, custom formats)
- Reduction Targets — View configured emissions reduction targets aligned with SBTi and net-zero commitments
The Watershed Climate MCP Server exposes 16 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.
How to Connect Watershed Climate to CrewAI via MCP
Follow these steps to integrate the Watershed Climate MCP Server with CrewAI.
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 16 tools from Watershed Climate
Why Use CrewAI with the Watershed Climate MCP Server
CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Watershed Climate 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 the 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
Watershed Climate + CrewAI Use Cases
Practical scenarios where CrewAI combined with the Watershed Climate MCP Server delivers measurable value.
Automated multi-step research: a reconnaissance agent queries Watershed Climate 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 Watershed Climate, analyzes trends over time, and generates executive briefings in markdown or PDF format
Multi-source enrichment pipelines: chain Watershed Climate 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 Watershed Climate against predefined policy rules, generates deviation reports, and routes findings to the appropriate team
Watershed Climate MCP Tools for CrewAI (16)
These 16 tools become available when you connect Watershed Climate to CrewAI via MCP:
create_upload
An upload is required before you can add data records to Watershed. After creating an upload, you add data records to it, validate the data, and then submit it for processing. The upload acts as a batch grouping mechanism for related activity data. You can optionally provide a name and description to identify the upload purpose. Create a new data upload container in Watershed
delete_upload_data_record
Use this to remove incorrect or unwanted data before validating and submitting the upload. This action cannot be undone. The record_id is obtained from list_upload_data_records. Delete a specific data record from an upload
get_inventory
Use the inventory_id from list_inventories to inspect detailed carbon footprint results and understand your organization's emissions composition. Get detailed information about a specific GHG inventory
get_report
Use the report_id from list_reports to access the full report details including generated files, disclosure frameworks covered, and emissions data summarized. Reports are typically generated after inventories are complete and validated. Get detailed information about a specific report
get_task_status
When you submit an upload for processing, a task is created and returns a task_id. Use this tool to check if the processing is complete, still in progress, or failed. Task status is useful for monitoring large data submissions that may take time to process. Check status of a processing task (e.g., upload submission)
get_upload
Use the upload_id from list_uploads to inspect details before adding data or submitting for validation. Get details of a specific data upload
list_inventories
An inventory represents your organization's carbon footprint measurement for a specific year, containing Scope 1 (direct), Scope 2 (energy), and Scope 3 (value chain) emissions data. Each inventory has a year, status, and total emissions calculated from submitted activity data. List all GHG inventories in your Watershed organization
list_measurements
Measurements represent the actual carbon footprint values derived from your uploaded activity data. You can filter by inventory_id to see measurements for a specific year's inventory, or by year to see measurements across all inventories for that year. Each measurement includes the activity type, emission factor used, and calculated CO2e value. List emissions measurements with optional filters
list_reduction_targets
Reduction targets define your organization's goals for decreasing emissions over time, often aligned with Science Based Targets initiative (SBTi) or net-zero commitments. Each target includes baseline year, target year, reduction percentage, and progress tracking. List all emissions reduction targets configured in your organization
list_reports
Reports are formatted outputs of your climate data for disclosure, analysis, or internal review. Reports can include CDP disclosures, TCFD reports, or custom carbon footprint summaries. Each report has metadata about its type, generation date, and scope. List all available reports in your Watershed organization
list_upload_data_records
Each record contains the activity data that will be processed into emissions measurements. Use this to review the data before validating and submitting the upload. List all data records in a specific upload
list_uploads
Uploads are containers for activity data that will be validated and processed into emissions measurements. Each upload can contain multiple data records representing activities like electricity usage, flights, or shipping. Use this to see all existing uploads and their IDs before adding data or submitting for processing. List all data uploads in your Watershed organization
submit_upload
This triggers Watershed's calculation engine to convert activity data into emissions measurements using appropriate emission factors. The upload must be validated successfully before submission. The response includes a task_id that can be used to track processing status via get_task_status. Processing may take some time depending on data volume. Submit a validated upload for emissions processing
update_upload_data_record
Use this to correct errors or modify activity data before validation and submission. The record_id is obtained from list_upload_data_records. The body should contain the complete updated record object with all required fields. Update a specific data record in an upload
upload_data_records
Each record represents an activity that generates emissions (e.g., electricity consumption, business travel, shipping). Records should follow Watershed's data format with fields like: activity_type, quantity, unit, start_date, end_date, location, etc. You can upload a single record or multiple records in a batch by providing an array of objects. Example record: { "activity_type": "electricity", "quantity": 1500, "unit": "kWh", "start_date": "2024-01-01", "end_date": "2024-01-31" } Upload activity data records to an existing upload container
validate_upload
Validation ensures data quality and prevents rejection during the submission phase. The response includes validation results with any errors or warnings that need to be addressed. Always validate before submitting to ensure successful processing. Validate data in an upload before submission
Example Prompts for Watershed Climate in CrewAI
Ready-to-use prompts you can give your CrewAI agent to start working with Watershed Climate immediately.
"List all our GHG inventories and show me the total emissions for 2024."
"Create a new upload called 'Q1 2024 Electricity Data', add these 3 records: electricity usage for NYC office (50,000 kWh), London office (35,000 kWh), and São Paulo office (28,000 kWh) for January 2024, then validate and submit it."
"Show me our reduction targets and current progress toward our net-zero goal."
Troubleshooting Watershed Climate MCP Server with CrewAI
Common issues when connecting Watershed Climate to CrewAI through the Vinkius, and how to resolve them.
MCP tools not discovered
Agent not using tools
Timeout errors
Rate limiting or 429 errors
Watershed Climate + CrewAI FAQ
Common questions about integrating Watershed Climate MCP Server with CrewAI.
How does CrewAI discover and connect to MCP tools?
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?
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?
Can CrewAI agents call multiple MCP tools in parallel?
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)?
crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.Connect Watershed Climate with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Watershed Climate to CrewAI
Get your token, paste the configuration, and start using 16 tools in under 2 minutes. No API key management needed.