by TakoData
Provides a simple MCP server that queries Tako for real-time data and generates visualizations.
Tako MCP enables you to query the Tako platform for up‑to‑date information and instantly turn that data into visualizations (embeds, webpages, images) via Model Context Protocol tools.
TAKO_API_KEY.uv run main.py).mcp.json.search_tako, upload_file_to_visualize, visualize_file, or visualize_dataset from your prompts.generate_search_tako_prompt, generate_visualization_prompt) assist users in crafting optimal queries and visualization requests.ENVIRONMENT=remote and ENVIRONMENT=local to run the server where needed.Q: Where do I get the Tako API key? A: Sign in to the Tako Dashboard (https://trytako.com/dashboard) and copy the key from the API section.
Q: Do I need a specific Python environment?
A: The project uses uv for dependency management; running uv sync will set up required packages.
Q: How do I run the server in remote mode?
A: Set the environment variable ENVIRONMENT=remote before starting the server, e.g., ENVIRONMENT=remote TAKO_API_KEY=… uv run main.py.
Q: Can I test the tools without writing code?
A: Yes, use the Model Context Protocol Inspector (npx @modelcontextprotocol/inspector@latest) to connect to the running MCP and invoke tools interactively.
Q: What if I need to visualize large files?
A: Use the upload_file_to_visualize tool sparingly; for large files, the README recommends the Tako Playground (https://trytako.com/playground).
Tako MCP is a simple MCP server that queries Tako and returns real-time data and visualization
Check out Tako and our documentation
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.
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
Use the file_id from upload_file_to_visualize and visualize the file. Returns embed, webpage, and image url of the visualization
Takes a Tako Data Format data and visualize. Returns embed, webpage, and image url of the visualization
Prompt to assist the client to format query and search Tako using search_tako tool
Prompt to assist the client to transform the data into Tako Data Format and visualize using visualize_dataset tool
Access Tako Dashboard and get your API key.
To install tako-mcp for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @TakoData/tako-mcp --client claude
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>"
}
}
}
}
generate_search_tako_promptThe prompt will guide the model to generate optimized query to search Tako
Add an input text to generate the prompt
"Compare Magnificent 7 stock companies on relevant metrics."
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
ENVIRONMENTOptions:
remote - If you're running a remote MCP serverlocal - If you're running a local MCP serverTAKO_API_KEYStart 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
Since we use uv Render uses pip, we have to build a requirements.txt
uv pip compile pyproject.toml > requirements.txt
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{
"mcpServers": {
"tako-mcp": {
"command": "uv",
"args": [
"--directory",
"/path/to/tako/mcp",
"run",
"main.py"
],
"env": {
"TAKO_API_KEY": "<YOUR_API_KEY>"
}
}
}
}claude mcp add tako-mcp uv --directory /path/to/tako/mcp run main.pyExplore related MCPs that share similar capabilities and solve comparable challenges
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