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Jitsu

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Jitsu is an open-source Segment alternative. Fully-scriptable data ingestion engine for modern data teams. Set-up a real-time data pipeline in minutes, not days

Publisherjitsucom
Repositoryjitsu
LanguageTypeScript
Forks
398
Stars
5.1K
Available tools
0
Transport typestdio
Categories
LicenseMIT
Links
  • Connect tools to AI workflows

    Jitsu exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    5.1K stars and 398 forks from the linked repository.


What is Jitsu?

Jitsu collects event data from your websites, apps and servers, and delivers it to your data warehouse and to whatever other tools you use. It covers the same ground as Segment, but it's MIT-licensed and self-hostable, so the whole pipeline can run inside your own infrastructure — or on Jitsu Cloud, same software, hosted.

Data lands in minutes, not hours: Segment loads warehouses once or twice a day (hourly at best), while Jitsu delivers per destination in batches as frequent as a minute, or row-by-row where that suits the destination. And where Segment bills by Monthly Tracked User, Jitsu Cloud bills by event volume, so the bill tracks data rather than audience size — while self-hosting has no usage billing at all.

A typical Jitsu setup gives you:

  • Event collection from the browser, mobile, or the server, via SDKs, an HTTP API, or a drop-in Segment proxy.
  • Delivery to destinations — ClickHouse, BigQuery, Snowflake, Redshift, Postgres, S3, GCS, and dozens of SaaS tools, streamed or micro-batched depending on what the destination prefers. See the destination catalog.
  • Functions — JavaScript that runs on every event to filter, transform, and enrich it before delivery.
    • Write them in the browser, or build and deploy them from your own repo with the Jitsu CLIjitsu-cli init scaffolds a TypeScript project with tests, and jitsu-cli deploy ships it to your workspace. Use whatever tooling you like: TypeScript, npm libraries, your own test suite, and your normal CI.
  • Connector syncs — pull data into your warehouse from third-party sources (Airbyte-compatible connectors).
  • A user identity graph and profile builder, built automatically from the event stream.
  • Live Events — see every event, function log and destination write as it happens, which makes debugging a pipeline a matter of seconds rather than days.
  • An MCP server, so an AI agent can configure and operate all of the above.

Get started with Jitsu Cloud

The fastest way to run Jitsu is Jitsu Cloud — we host and scale it for you.

  • Free tier: 200k events/month, no credit card required.
  • Unlimited destinations and unlimited captured events on every plan.
  • A free ClickHouse instance is included, so you can go from zero to queryable event data without provisioning a warehouse first.
  • Custom domains, events debugger, and the Configuration API on the free tier too.

See pricing for the full breakdown, or jump straight into the Quick Start guide.

Once you have a workspace:

  1. Create a site (a stream) and grab your write key.
  2. Add a destination — ClickHouse, BigQuery, Snowflake, Postgres, S3, or anything from the catalog.
  3. Start sending events using one of the methods below.

Sending events

MethodUse it for
HTML snippetAny website, no build step
@jitsu/jsIsomorphic — works in the browser and in Node.js
@jitsu/jitsu-reactReact and Next.js apps
HTTP APIAny language, backend services
Segment proxyMigrating off Segment without touching client code

Everything the UI does is also available through the Management API and the Jitsu CLI.

Jitsu MCP Server

Jitsu ships a Model Context Protocol server, so coding agents and AI assistants can build and operate your data pipelines directly — no clicking through the UI.

An agent connected to Jitsu can set up a destination, wire a connection, send a test event, read the resulting Live Events, notice that a function threw, fix the function, and re-run it — the full loop, without a human in the middle.

Endpoint: https://use.jitsu.com/mcp (or <your-console-url>/mcp when self-hosting).

Connect your client

Claude Code

bash
claude mcp add --transport http jitsu https://use.jitsu.com/mcp

Other clients (Claude Desktop, Cursor, VS Code) take the same URL — see jitsu.com/docs/mcp for their setup.

Authentication

Interactive clients use OAuth 2.1 — no API key to manage. The first tool call opens a browser tab asking you to approve the connection; tokens are scoped, listed, and revocable from your account settings page.

Headless environments (CI, cron, servers) use a personal API key instead — generate one on the user settings page and pass it as Authorization: Bearer <keyId>:<keySecret>:

bash
claude mcp add --transport http jitsu https://use.jitsu.com/mcp \
  --header "Authorization: Bearer $JITSU_API_KEY"

What the agent can do

25 tools, covering everything the console does: read and write workspace configuration (destinations, streams, connections, functions), query Live Events and function logs, run and cancel connector syncs, discover source streams and inspect sync state, execute functions and profile builders against test data, and pull event and sync statistics. Full reference: jitsu.com/docs/mcp.

Architecture

Jitsu is a handful of independently scalable services:

ServiceStackWhat it does
ingestGoHTTP endpoint that accepts events and writes them to Kafka
rotorTypeScriptRoutes events, runs Functions, applies destination-specific transforms
bulkerGoHigh-throughput warehouse ingestion — batching, schema management, retries
sync-controllerGoOrchestrates connector syncs (pulling data from third-party sources)
consoleNext.jsAdmin UI, Management API, and the MCP server

Backed by Postgres (configuration), Kafka/Redpanda (event bus), ClickHouse (live events and metrics), and MongoDB (profiles).

Bulker is also usable standalone if you just want a warehouse ingestion engine and are comfortable with low-level APIs.

Self-hosting

Jitsu is MIT-licensed and fully self-hostable, with no usage limits and no feature gating. Cloud is the path of least resistance; self-hosting is for when you need the data to stay inside your own infrastructure.

Quick start (Kubernetes / Minikube)

The development Helm chart is the recommended way to get a complete stack running locally. You'll need Minikube (a single-node Kubernetes cluster on your machine) and Helm v3+:

bash
git clone -b newjitsu --single-branch https://github.com/jitsucom/jitsu
cd jitsu/helm

minikube start          # give the VM at least 8GB RAM
./dev-deploy.sh deploy
./dev-deploy.sh tunnel  # in a second terminal

./dev-deploy.sh tunnel runs minikube tunnel, which routes the cluster's LoadBalancer services to localhost so you can reach them from your browser — console on :3000, ingest on :3049, bulker on :3042, rotor on :3401, plus Postgres, ClickHouse, MongoDB and Kafka. It asks for sudo (it binds privileged ports) and has to keep running in its own terminal for the whole session.

The console will be at http://localhost:3000. Full instructions: Self-hosting Quick Start.

Production

For real deployments, read the Production Deployment guide and the Configuration Reference. It covers scaling each service, Kafka sizing, and the environment variables every component reads.

Contributing

Contributions are welcome. CONTRIBUTING.md covers the repository layout, how to set up a development environment and run the test suites, and the branch, commit and pull request conventions.

Community & support

  • Slack — the fastest way to reach the team and other users
  • GitHub Issues — bugs and feature requests
  • Docs — guides and reference

License

Jitsu is licensed under the MIT License.

Use Jitsu MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once Jitsu is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add Jitsu as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the Jitsu MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "jitsu": {
      "command": "npx",
      "args": [
        "-y",
        "<mcp-server-package>"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the Jitsu MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the Jitsu MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use Jitsu to help me with this task?
Jitsu
Sure. I read it.
Here is what I found using Jitsu.

Frequently asked questions

What is the Jitsu MCP server used for?

Jitsu is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use Jitsu MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use Jitsu with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use Jitsu MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With Jitsu connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect Jitsu MCP to TypingMind?

Jitsu runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does Jitsu MCP provide in TypingMind?

Jitsu exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use Jitsu MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If Jitsu requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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