Toronto

You can query, analyze, and retrieve Toronto Open Data datasets through a dedicated MCP server that leverages the CKAN API. It unlocks intelligent dataset discovery, update freshness analysis, deep schema insight, and natural language querying across Toronto’s 500+ open datasets, making it easy for MCP-compatible assistants to find and understand relevant data.

How to use

Connect your MCP client to the Toronto MCP Server to access intelligent data tools. Start by locating the MCP endpoint for remote access and use your client’s MCP integration to issue queries such as dataset discovery, update frequency analysis, and schema exploration. The server returns relevance-ranked results, frequency categorizations, and detailed data structures to help you interpret datasets and plan analyses. When you ask questions like What traffic data is available in Toronto? or Which datasets update daily?, you receive ranked datasets with context about freshness and structure.

How to install

Prerequisites: You need Node.js installed on your machine and an environment capable of running Cloudflare Workers tools. You should also have a working npm setup to install dependencies and deploy. Follow these steps to set up your own instance or validate an existing one.

npm install -g wrangler
wrangler login
wrangler whoami

# Clone your project repository
# Replace <your-repo> with your actual repo URL
git clone <your-repo>
cd toronto-mcp

# Install dependencies for the project
npm install

# Build or prepare the worker if required by your setup
# For development against Cloudflare Workers, you typically deploy directly
wrangler deploy

Configuration and usage notes

The Toronto MCP Server exposes a remote MCP endpoint that you can connect to from MCP clients. The live access point for the MCP interface is available at the following endpoint for programmatic access and automation.

https://toronto-mcp.s-a62.workers.dev/mcp

Troubleshooting and tips

If you encounter connectivity issues, verify that your MCP client is pointed at the correct endpoint and that the client can reach the server URL. Check network firewalls, and confirm that your client’s time settings are synchronized to avoid token or session timeouts. If you see delays on complex queries, consider simplifying the request or limiting the dataset scope to improve response times.

For client-side setup, you may need a Claude Desktop configuration to integrate with the server. Ensure your client points at the SSE endpoint for real-time streaming responses and uses the MCP endpoint for the primary query channel.

Notes

The server provides tools to list and retrieve dataset metadata, search datasets, access records, and perform advanced analyses such as relevance ranking, update frequency analysis, and data structure insights. Use these capabilities to build data-driven prompts and analyses for your research or application.

Available tools

list_datasets

List all available datasets from the Toronto CKAN portal.

search_datasets

Search datasets by keyword or phrase to refine results.

get_package

Retrieve complete metadata for a specific dataset package.

get_first_datastore_resource_records

Fetch records from the first active datastore resource of a dataset.

get_resource_records

Retrieve records from a specific resource by its ID.

find_relevant_datasets

Intelligently discover and rank datasets using relevance scoring across title, description, tags, and organization.

analyze_dataset_updates

Analyze update frequencies and categorize datasets by daily, weekly, monthly, quarterly, annually, or irregular patterns.

analyze_dataset_structure

Provide deep-dive schema insights including field definitions, data types, counts, and optional data previews.

get_data_categories

Explore all available organizations and topic groups within the data portal.

get_dataset_insights

Combine relevance, freshness, and structure to yield comprehensive dataset insights.