Tako MCP

Tako MCP is a simple MCP server that queries Tako and returns real-time data and visualization

Check out Tako and our documentation

Available Tools

search_tako

Takes a query to search Tako and the web to get real-time data and visualization. Returns embed, webpage, and image url of the visualization with relevant metadata such as source, methodology, and description.

upload_file_to_visualize

Takes a base64 encoded file as an input and uploads it to Tako to use for visualization

*If you call this tool with a big file, it may consume a large number of tokens and will be very slow. If you want to test visualizing bigger files though Tako, visit our playground

visualize_file

Use the file_id from upload_file_to_visualize and visualize the file. Returns embed, webpage, and image url of the visualization

visualize_dataset

Takes a Tako Data Format data and visualize. Returns embed, webpage, and image url of the visualization

Available Prompts

generate_search_tako_prompt

Prompt to assist the client to format query and search Tako using search_tako tool

generate_visualization_prompt

Prompt to assist the client to transform the data into Tako Data Format and visualize using visualize_dataset tool

Quickstart

Get your API key

Access Tako Dashboard and get your API key.

Installing via Smithery

To install tako-mcp for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @TakoData/tako-mcp --client claude

Add Tako MCP to Claude Desktop

Add the following to your .cursor/mcp.json or claude_desktop_config.json (MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json)

{
    "mcpServers": {
        "takoApi": {
            "command": "uv",
            "args": [
                "--directory",
                "/path/to/tako/mcp",
                "run",
                "main.py"
            ],
            "env": {
                "TAKO_API_KEY": "<TAKO_API_KEY>"
            }
        }
    }
}

Example:

1. Use the prompt from Tako MCP Server generate_search_tako_prompt

The prompt will guide the model to generate optimized query to search Tako

2. Add your text input

Add an input text to generate the prompt

"Compare Magnificent 7 stock companies on relevant metrics."

3. Add a prompt to the chat

Add additional instructions to the chat prompt

Write me a research report on the magnificent 7 companies. Embed the result in an iframe whenever necessary

4. Checkout the result

• Claude Response
• Generated Report

Environment Variables

ENVIRONMENT

Options:

• remote - If you're running a remote MCP server
• local - If you're running a local MCP server

TAKO_API_KEY

• Your Tako API key, access it from Tako Dashboard

Testing Remote MCP

Start inspector and access the console

npx -y npx @modelcontextprotocol/inspector@latest

Start Tako MCP Server on remote mode

ENVIRONMENT=remote TAKO_API_KEY=<your_tako_api_key> uv run main.py

In inspector console, add the url https://0.0.0.0:<port>/mcp/ and click connect

Select the Tools tab, and click ListTools.

Select search_tako and test a query

Deploying it on render

Since we use uv Render uses pip, we have to build a requirements.txt

uv pip compile pyproject.toml > requirements.txt