Tinybird Mcp Server

Created by

tinybirdco•Jul 4, 2025

Mcp Tinybird

Overview

What is MCP-Tinybird?

MCP-Tinybird is an open-source project hosted on GitHub under the organization Tinybirdco. It serves as a powerful tool for developers looking to build and manage data pipelines efficiently. The repository is designed to facilitate the integration of Tinybird's capabilities into various applications, allowing users to leverage real-time data processing and analytics.

Features of MCP-Tinybird

Real-time Data Processing: MCP-Tinybird enables users to process and analyze data in real-time, making it ideal for applications that require immediate insights.
User-Friendly Interface: The project offers a straightforward interface that simplifies the management of data pipelines, making it accessible for developers of all skill levels.
Open Source: Being an open-source project, MCP-Tinybird encourages community contributions and collaboration, allowing developers to enhance its features and functionality.
Integration Capabilities: The repository supports integration with various data sources and services, providing flexibility in how data is ingested and processed.
Documentation and Support: Comprehensive documentation is available to assist users in getting started and troubleshooting any issues they may encounter.

How to Use MCP-Tinybird

Clone the Repository: Begin by cloning the MCP-Tinybird repository from GitHub to your local machine using the command:
```
git clone https://github.com/tinybirdco/mcp-tinybird.git
```
Install Dependencies: Navigate to the project directory and install the necessary dependencies. This can typically be done using a package manager like npm or yarn:
```
cd mcp-tinybird
npm install
```
Configure Your Environment: Set up your environment variables and configuration files as per the documentation provided in the repository.
Run the Application: Start the application to begin processing data. This can usually be done with a command like:
```
npm start
```
Explore and Customize: Utilize the features of MCP-Tinybird to build your data pipelines. You can customize the application based on your specific needs and integrate it with other services.

Frequently Asked Questions

Q1: Is MCP-Tinybird free to use?

A1: Yes, MCP-Tinybird is an open-source project, which means it is free to use and modify under the terms of the Apache-2.0 license.

Q2: Can I contribute to the MCP-Tinybird project?

A2: Absolutely! Contributions are welcome. You can fork the repository, make your changes, and submit a pull request for review.

Q3: Where can I find the documentation for MCP-Tinybird?

A3: Documentation is available in the repository itself, typically in a README.md file or a dedicated docs folder.

Q4: What technologies does MCP-Tinybird support?

A4: MCP-Tinybird is designed to work with various data sources and can integrate with multiple technologies, enhancing its versatility for different use cases.

Q5: How can I report issues or bugs?

A5: You can report issues by navigating to the "Issues" tab in the MCP-Tinybird GitHub repository and submitting a new issue with detailed information about the problem.

Details

Tinybird MCP server

An MCP server to interact with a Tinybird Workspace from any MCP client.

Features

Query Tinybird Data Sources using the Tinybird Query API
Get the result of existing Tinybird API Endpoints with HTTP requests
Push Datafiles

It supports both SSE and STDIO modes.

Usage examples

Setup

Installation

Using MCP package managers

Smithery

To install Tinybird MCP for Claude Desktop automatically via Smithery:

npx @smithery/cli install @tinybirdco/mcp-tinybird --client claude

mcp-get

You can install the Tinybird MCP server using mcp-get:

npx @michaellatman/mcp-get@latest install mcp-tinybird

Prerequisites

MCP is still very new and evolving, we recommend following the MCP documentation to get the MCP basics up and running.

You'll need:

Configuration

1. Configure Claude Desktop

Create the following file depending on your OS:

On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json

On Windows: %APPDATA%/Claude/claude_desktop_config.json

Paste this template in the file and replace <TINYBIRD_API_URL> and <TINYBIRD_ADMIN_TOKEN> with your Tinybird API URL and Admin Token:

{
    "mcpServers": {
        "mcp-tinybird": {
            "command": "uvx",
            "args": [
                "mcp-tinybird",
                "stdio"
            ],
            "env": {
                "TB_API_URL": "<TINYBIRD_API_URL>",
                "TB_ADMIN_TOKEN": "<TINYBIRD_ADMIN_TOKEN>"
            }
        }
    }
}

2. Restart Claude Desktop

SSE mode

Alternatively, you can run the MCP server in SSE mode by running the following command:

uvx mcp-tinybird sse

This mode is useful to integrate with an MCP client that supports SSE (like a web app).

Prompts

The server provides a single prompt:

tinybird-default: Assumes you have loaded some data in Tinybird and want help exploring it.
- Requires a "topic" argument which defines the topic of the data you want to explore, for example, "Bluesky data" or "retail sales".

You can configure additional prompt workflows:

Create a prompts Data Source in your workspace with this schema and append your prompts. The MCP loads prompts on initialization so you can configure it to your needs:

SCHEMA >
    `name` String `json:$.name`,
    `description` String `json:$.description`,
    `timestamp` DateTime `json:$.timestamp`,
    `arguments` Array(String) `json:$.arguments[:]`,
    `prompt` String `json:$.prompt`

Tools

The server implements several tools to interact with the Tinybird Workspace:

list-data-sources: Lists all Data Sources in the Tinybird Workspace
list-pipes: Lists all Pipe Endpoints in the Tinybird Workspace
get-data-source: Gets the information of a Data Source given its name, including the schema.
get-pipe: Gets the information of a Pipe Endpoint given its name, including its nodes and SQL transformation to understand what insights it provides.
request-pipe-data: Requests data from a Pipe Endpoints via an HTTP request. Pipe endpoints can have parameters to filter the analytical data.
run-select-query: Allows to run a select query over a Data Source to extract insights.
append-insight: Adds a new business insight to the memo resource
llms-tinybird-docs: Contains the whole Tinybird product documentation, so you can use it to get context about what Tinybird is, what it does, API reference and more.
save-event: This allows to send an event to a Tinybird Data Source. Use it to save a user generated prompt to the prompts Data Source. The MCP server feeds from the prompts Data Source on initialization so the user can instruct the LLM the workflow to follow.
analyze-pipe: Uses the Tinybird analyze API to run a ClickHouse explain on the Pipe Endpoint query and check if indexes, sorting key, and partition key are being used and propose optimizations suggestions
push-datafile: Creates a remote Data Source or Pipe in the Tinybird Workspace from a local datafile. Use the Filesystem MCP to save files generated by this MCP server.

Development

Config

If you are working locally add two environment variables to a .env file in the root of the repository:

TB_API_URL=
TB_ADMIN_TOKEN=

For local development, update your Claude Desktop configuration:

{
  "mcpServers": {
    "mcp-tinybird_local": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/your/mcp-tinybird",
        "run",
        "mcp-tinybird",
        "stdio"
      ]
    }
  }
}

<details> <summary>Published Servers Configuration</summary>

"mcpServers": {
  "mcp-tinybird": {
    "command": "uvx",
    "args": [
      "mcp-tinybird"
    ]
  }
}

</details>

Building and Publishing

To prepare the package for distribution:

Sync dependencies and update lockfile:

uv sync

Build package distributions:

uv build

This will create source and wheel distributions in the dist/ directory.

Publish to PyPI:

uv publish

Note: You'll need to set PyPI credentials via environment variables or command flags:

Token: --token or UV_PUBLISH_TOKEN
Or username/password: --username/UV_PUBLISH_USERNAME and --password/UV_PUBLISH_PASSWORD

Debugging

Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.

You can launch the MCP Inspector via npm with this command:

npx @modelcontextprotocol/inspector uv --directory /Users/alrocar/gr/mcp-tinybird run mcp-tinybird

Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.

Monitoring

To monitor the MCP server, you can use any compatible Prometheus client such as Grafana. Learn how to monitor your MCP server here.

Server Config

{
  "mcpServers": {
    "mcp-tinybird": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/metorial/mcp-container--tinybirdco--mcp-tinybird--mcp-tinybird",
        "mcp-tinybird stdio"
      ],
      "env": {
        "TB_API_URL": "tb-api-url",
        "TB_ADMIN_TOKEN": "tb-admin-token"
      }
    }
  }
}

Project Info

Author

tinybirdco