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mindsdb

The unified workspace where open-source models get things done for you.

Publishermindsdb
Repositorymindshub
LanguageMakefile
Forks
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Stars
39.8K
Available tools
0
Transport typestdio
LicenseMIT
Links
  • Connect tools to AI workflows

    Mindshub 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

    39.8K stars and 6.2K forks from the linked repository.

MindsHub is an agent workspace for completing knowledge work and developing software, with open-source agent harnesses and a choice of models.

Release Stars License: MIT Python 3.10–3.13

Website · Docs · Web app · Pricing · Discord

MindsHub gives you the freedom to choose among models and providers instead of being locked into one ecosystem. Use its agent workspace for research, analysis, content creation, and software development. It is open source and can run on your machine, in your VPC, or through the hosted app.

This repository is the platform superproject: it pulls together the desktop/web app, the agent backend, and the data engine so you can build and run the whole stack from source.

For building intelligence into agents and products through one API, see MindsHub Inference. It provides a choice of models and providers with one set of controls and one bill.

Get started

Pick whichever fits:

Free to start. Pro adds all frontier models and private artifacts — see pricing.

What you can do

For every knowledge worker — creators, strategists, and operators:

  • Automate repetitive, multi-step work that involves reading and writing: reports, monitoring, recurring workflows, and scheduled operations.
  • Build internal AI tools and artifacts — apps, dashboards, decks, docs, analyses — without engineering, and publish them to a live URL to share with your team.

What's inside

  • Connected data. A secure vault links systems like BigQuery, Postgres, Gmail, Drive, HubSpot, Notion, and Linear. Credentials stay scoped per connection — agents never see raw keys.
  • Model Router. Switch between frontier models (Claude, GPT, Gemini) and open models (DeepSeek, Qwen, Kimi) without wiring up a key for each provider.
  • Open agents. Run interchangeable open-source harnesses — Anton (default) and Hermes — swappable from a dropdown.
  • Artifacts. Turn agent output into documents, dashboards, apps, and code, and publish to a live URL.
  • Memory, skills & scheduling. Cross-session memory, a reusable skill library, and tasks that run on a schedule.

Build from source

1. Clone the repository

bash
git clone --recurse-submodules https://github.com/mindsdb/minds.git
cd minds

2. Install dependencies

bash
make setup

3. Run

ModeCommand
Desktop app (Electron) with hot reloadmake dev or make watch
Web app in browser with hot reloadmake dev-web
Production buildmake build
Package for macOSmake dist-mac
Package for Windowsmake dist-win
Build macOS .app from local uncommitted sourcemake pack-local
Wipe all local installs + data (fresh start)make flush

Fresh start: make flush removes the local runtime (the cowork-server uv tool and the backend/*/.venvs) and deletes app state in ~/.anton (provider keys) and ~/.cowork (database, hermes, projects). Use it to test the from-scratch install flow or recover from a broken install. It prompts for confirmation — pass FORCE=1 to skip. The next make setup or app launch reinstalls everything. ⚠️ This deletes your conversations and saved keys.

Working on feature branches (submodules)

This repo is a superproject that pins each module (frontend, backend/core_api, backend/core_agent, backend/data-vault) to a commit. To work on module branches without polluting git status or fighting over pins:

1. Pick your branches in a gitignored dev.env (copy the template):

bash
cp dev.env.example dev.env      # then set REF=feat/my-thing (or per-module API_REF=…)

2. make follows it — one knob, both run paths:

CommandWhat it does
make usecheck out your dev.env refs across all submodules
make dev / make watchrun the Electron app with live reload against local source
make dev-webrun the web SPA with live reload against local source
make server + make app(re)install the desktop server from the configured branch, then launch
make server-local + make app-localinstall the desktop server from local uncommitted source, then launch
make pack-localbuild the macOS .app from local uncommitted source (no push needed)
make refsshow which refs the next run will use
make baselinereset submodules to the pinned commits
make pinrecord the current submodule commits as the superproject's pins (one deliberate commit)

Submodules are configured with ignore = all, so your branch work never shows up as superproject changes — the parent git status stays clean. Pins move only via make pin. See CLAUDE.md for the full workflow.

Deploy anywhere

MindsHub is built for flexible deployment — cloud, VPC, on-prem, air-gapped, and hybrid infrastructure — so you keep full control over your infrastructure, models, permissions, and data.

Help & support

🤝 Contribute

MindsHub is open source and contributions are welcome — code, integrations, docs, bug reports, and feature ideas. Read the docs to get set up, browse open issues, and say hi on Discord.

🔒 Security

Found a security vulnerability? Please don't open a public issue. Report it privately through our security policy.

📚 Resources

📄 License

This repository is released under the MIT License. Bundled components are governed by their own licenses — see each submodule's repository for details.

Use Mindshub MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once Mindshub 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 Mindshub 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 Mindshub 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": {
    "mindshub": {
      "command": "npx",
      "args": [
        "-y",
        "<mcp-server-package>"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the Mindshub 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 Mindshub 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 Mindshub to help me with this task?
Mindshub
Sure. I read it.
Here is what I found using Mindshub.

Frequently asked questions

What is the Mindshub MCP server used for?

Mindshub 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 Mindshub MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use Mindshub 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 Mindshub 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 Mindshub connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect Mindshub MCP to TypingMind?

Mindshub 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 Mindshub MCP provide in TypingMind?

Mindshub 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 Mindshub MCP?

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

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