Watershed Climate MCP Server for LlamaIndex 16 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Watershed Climate as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Watershed Climate. "
"You have 16 tools available."
),
)
response = await agent.run(
"What tools are available in Watershed Climate?"
)
print(response)
asyncio.run(main())
* 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.
LlamaIndex agents combine Watershed Climate tool responses with indexed documents for comprehensive, grounded answers. Connect 16 tools through the Vinkius and query live data alongside vector stores and SQL databases in a single turn — ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex via MCP
Follow these steps to integrate the Watershed Climate MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 16 tools from Watershed Climate
Why Use LlamaIndex with the Watershed Climate MCP Server
LlamaIndex provides unique advantages when paired with Watershed Climate through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Watershed Climate tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Watershed Climate tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Watershed Climate, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Watershed Climate tools were called, what data was returned, and how it influenced the final answer
Watershed Climate + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Watershed Climate MCP Server delivers measurable value.
Hybrid search: combine Watershed Climate real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Watershed Climate to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Watershed Climate for fresh data
Analytical workflows: chain Watershed Climate queries with LlamaIndex's data connectors to build multi-source analytical reports
Watershed Climate MCP Tools for LlamaIndex (16)
These 16 tools become available when you connect Watershed Climate to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting Watershed Climate to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpWatershed Climate + LlamaIndex FAQ
Common questions about integrating Watershed Climate MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
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 LlamaIndex
Get your token, paste the configuration, and start using 16 tools in under 2 minutes. No API key management needed.