Tako MCP Server

An MCP (Model Context Protocol) server that provides access to Tako's knowledge base and interactive data visualizations.

# What is this?

This MCP server enables AI agents to:

• Search Tako's knowledge base for charts and data visualizations
• Fetch chart preview images and AI-generated insights
• Render fully interactive Tako charts via MCP-UI

# Installation

pip install tako-mcp

Or install from source:

git clone https://github.com/anthropics/tako-mcp.git
cd tako-mcp
pip install -e .

# Quick Start

# # Get an API Token

Sign up at trytako.com and create an API token in your account settings.

# # Run the Server

tako-mcp

Or with Docker:

docker build -t tako-mcp .
docker run -p 8001:8001 tako-mcp

# # Connect Your Agent

Point your MCP client to http://localhost:8001.

# Available Tools

# # knowledge_search

Search Tako's knowledge base for charts and data visualizations.

{
  "query": "Intel vs Nvidia headcount",
  "api_token": "your-api-token",
  "count": 5,
  "search_effort": "deep"
}

Returns matching charts with IDs, titles, descriptions, and URLs.

# # get_chart_image

Get a preview image URL for a chart.

{
  "pub_id": "chart-id",
  "api_token": "your-api-token",
  "dark_mode": true
}

# # get_card_insights

Get AI-generated insights for a chart.

{
  "pub_id": "chart-id",
  "api_token": "your-api-token",
  "effort": "medium"
}

Returns bullet-point insights and a natural language description.

# # explore_knowledge_graph

Discover available entities, metrics, and cohorts.

{
  "query": "tech companies",
  "api_token": "your-api-token",
  "limit": 20
}

# ThinViz API - Create Custom Charts

ThinViz lets you create charts with your own data using pre-configured templates.

# # list_chart_schemas

List available chart templates.

{
  "api_token": "your-api-token"
}

Returns schemas like stock_card, bar_chart, grouped_bar_chart.

# # get_chart_schema

Get detailed info about a schema including required components.

{
  "schema_name": "bar_chart",
  "api_token": "your-api-token"
}

# # create_chart

Create a chart from a template with your data.

{
  "schema_name": "bar_chart",
  "api_token": "your-api-token",
  "source": "Company Reports",
  "components": [
    {
      "component_type": "header",
      "config": {
        "title": "Revenue by Region",
        "subtitle": "Q4 2024"
      }
    },
    {
      "component_type": "categorical_bar",
      "config": {
        "datasets": [{
          "label": "Revenue",
          "data": [
            {"x": "North America", "y": 120},
            {"x": "Europe", "y": 98},
            {"x": "Asia", "y": 156}
          ],
          "units": "$M"
        }],
        "title": "Revenue by Region"
      }
    }
  ]
}

Returns the new chart's card_id, embed_url, and image_url.

# MCP-UI - Interactive Charts

# # open_chart_ui

Open an interactive chart in the UI (MCP-UI).

{
  "pub_id": "chart-id",
  "dark_mode": true,
  "width": 900,
  "height": 600
}

Returns a UIResource for rendering an interactive iframe.

# Configuration

Environment variables:

| Variable | Description | Default |
|- -- -- -- -- -|- -- -- -- -- -- --|- -- -- -- --|
| TAKO_API_URL | Tako API endpoint | https://api.trytako.com |
| PUBLIC_BASE_URL | Public URL for chart embeds | https://trytako.com |
| PORT | Server port | 8001 |
| HOST | Server host | 0.0.0.0 |
| MCP_ALLOWED_HOSTS | Additional allowed hosts (comma-separated) | |
| MCP_ENABLE_DNS_REBINDING | Enable DNS rebinding protection | true |

# Testing

Run the test client:

python -m tests.test_client - -api-token YOUR_API_TOKEN

This verifies:

• MCP handshake and initialization
• Tool discovery
• Search, images, and insights
• MCP-UI resource generation

# Example Flow

1. User asks: "Show me a chart about Intel vs Nvidia headcount"
2. Agent calls knowledge_search with the query
3. Agent receives chart results with IDs
4. Agent can:
   • Call get_card_insights to summarize the data
   • Call get_chart_image for a preview
   • Call open_chart_ui to render an interactive chart

# Health Checks

• GET /health - Simple "ok" response
• GET /health/detailed - JSON with status and timestamp

# Architecture

AI Agent (LangGraph, CopilotKit, etc.)
    ↓
  MCP Protocol (SSE)
    ↓
Tako MCP Server
    ↓
Tako API

The server acts as a thin proxy that:

1. Authenticates requests with your API token
2. Translates MCP tool calls to Tako API requests
3. Returns formatted results and UI resources

# MCP-UI Support

The open_chart_ui tool returns an MCP-UI resource that clients can render as an interactive iframe. The embedded chart supports:

• Zooming and panning
• Hover interactions
• Responsive resizing via postMessage
• Light and dark themes

Clients that support MCP-UI (like CopilotKit) will automatically render these resources.

# License

MIT License - see LICENSE for details.

# Links

• Tako - Data visualization platform
• MCP Specification - Model Context Protocol
• MCP-UI - MCP UI rendering standard