Toronto Open Data MCP Server

by vduquette

282 downloads

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GitHub

Description

# Toronto Open Data MCP Server An MCP (Model Context Protocol) server that provides direct access to Toronto's Open Data through the CKAN API. This server allows LLM agents to efficiently discover, explore, and query Toronto's 500+ public datasets. ## Features - 🧠 **Intelligent…

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Details

Author: vduquette
Downloads: 282
Categories: Search

- Intelligent Query Engine that automatically finds and returns relevant data.
- Relevance scoring to rank datasets by question relevance.
- Smart filtering based on context (recent data, failures, locations).
- Adaptive data processing for real‑time API and CSV data.
- Agent‑optimized design for minimal LLM decision complexity.
- Robust deployment ready with health checks for Railway/cloud.

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name Toronto Open Data MCP Server

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "toronto open data mcp server": {
            "toronto-open-data-mcp-server": {
                "command": "python",
                "args": [
                    "main.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "toronto open data mcp server": {
            "toronto-open-data-mcp-server": {
                "command": "python",
                "args": [
                    "main.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "toronto open data mcp server": {
            "toronto-open-data-mcp-server": {
                "command": "python",
                "args": [
                    "main.py"
                ]
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "toronto open data mcp server": {
            "toronto-open-data-mcp-server": {
                "command": "python",
                "args": [
                    "main.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "toronto open data mcp server": {
            "toronto-open-data-mcp-server": {
                "command": "python",
                "args": [
                    "main.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "toronto open data mcp server": {
            "toronto-open-data-mcp-server": {
                "command": "python",
                "args": [
                    "main.py"
                ]
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "toronto open data mcp server": {
            "toronto-open-data-mcp-server": {
                "command": "python",
                "args": [
                    "main.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "toronto open data mcp server": {
            "toronto-open-data-mcp-server": {
                "command": "python",
                "args": [
                    "main.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "toronto open data mcp server": {
            "toronto-open-data-mcp-server": {
                "command": "python",
                "args": [
                    "main.py"
                ]
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "toronto open data mcp server": {
            "toronto-open-data-mcp-server": {
                "command": "python",
                "args": [
                    "main.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "toronto open data mcp server": {
            "toronto-open-data-mcp-server": {
                "command": "python",
                "args": [
                    "main.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "toronto open data mcp server": {
            "toronto-open-data-mcp-server": {
                "command": "python",
                "args": [
                    "main.py"
                ]
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "toronto open data mcp server": {
            "toronto-open-data-mcp-server": {
                "command": "python",
                "args": [
                    "main.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "toronto open data mcp server": {
            "toronto-open-data-mcp-server": {
                "command": "python",
                "args": [
                    "main.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "toronto open data mcp server": {
            "toronto-open-data-mcp-server": {
                "command": "python",
                "args": [
                    "main.py"
                ]
            }
        }
    }
}

From the repository

Clone the repository, install dependencies with pip install -e ., then run python main.py. The primary tool is toronto_find_and_query_data(user_question), a one-step solution that finds and processes the most relevant data. Alternative tools include toronto_start_here(), toronto_search_datasets(query), and toronto_smart_data_helper(dataset_id, user_question).

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "toronto open data mcp server": {
            "toronto-open-data-mcp-server": {
                "command": "python",
                "args": [
                    "main.py"
                ]
            }
        }
    }
}

McpServers

{
    "toronto-open-data-mcp-server": {
        "command": "python",
        "args": [
            "main.py"
        ]
    }
}

Toronto Open Data MCP Server

An MCP (Model Context Protocol) server that provides direct access to Toronto's Open Data through the CKAN API. This server allows LLM agents to efficiently discover, explore, and query Toronto's 500+ public datasets.

Features

- 🧠 Intelligent Query Engine: One-tool solution that automatically finds, processes, and returns relevant Toronto data
- 🎯 Relevance Scoring: Automatically ranks datasets by relevance to your question
- 🔍 Smart Filtering: Applies intelligent filters based on question context (recent data, failures, locations)
- 📊 Adaptive Data Processing: Handles both real-time API data and downloadable CSV files seamlessly
- 🚀 Agent-Optimized: Designed specifically for LLM agents with minimal decision complexity
- ✅ Robust Deployment: Ready for Railway/cloud deployment with health checks

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/toronto-open-data-mcp-server.git

   cd toronto-open-data-mcp-server

2. Install dependencies:

   # Install main dependencies

   pip install -e .

   

   # Install test dependencies (optional)

   pip install -e ".[test]"

3. Run the server:

   python main.py

Usage

Quick Start

Primary Tool (Recommended):
- toronto_find_and_query_data(user_question) - One-step solution that finds and processes the most relevant data

Alternative Tools:
- toronto_start_here() - Get usage guidance and workflow explanation
- toronto_search_datasets(query) - Manual dataset discovery
- toronto_smart_data_helper(dataset_id, user_question) - Process specific datasets

Example Usage

```python

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Setting up with Highlight

From the repository

Claude Desktop / Cursor

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Toronto Open Data MCP Server

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Example Usage

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