Generalbots MCP Server

<p align="center"><img src="logo.svg" alt="General Bots" width="200"></p>

General Bots

Multi-agent AI platform for autonomous agents, agentic AI orchestration and LLM workflow automation.

Self-hosted, open source, and built in Rust. General Bots gives you 80 sovereign applications — Chat, CRM, Mail, Drive, Calendar, Meetings, Documents and Advanced RAG — that run as one platform on your own infrastructure. Your cloud, your data, your rules.

Website · Documentation · Features · Blog · BotBook

<a href="https://github.com/generalbots/generalbots/graphs/contributors"> <img src="https://contrib.rocks/image?repo=generalbots/generalbots" alt="Contributors to General Bots" /> </a>

---

What it looks like

Two surfaces on one platform: the desktop suite where people work, and the cloud console where an organisation is run.

Desktop suite — :3000

<a href="generalbots-desktop.png"><img src="generalbots-desktop.png" alt="The General Bots desktop suite in its light theme, filling a browser window" width="100%"></a>

Every application opens as a window inside one desktop shell, so Chat, CRM, Drive, Mail, Calendar and Meetings sit side by side instead of in separate browser tabs. A theme manager switches the whole workspace between light, dark and wallpapered variants; the capture above is the light one. The suite is a plain web client served by botui, and the same client runs unchanged inside the Tauri wrapper (botapp) on desktop and mobile.

Cloud console — :4000

<a href="generalbots-cloud.png"><img src="generalbots-cloud.png" alt="The General Bots cloud console in its dark theme, filling a browser window" width="100%"></a>

The control plane for running General Bots as a service: the store, plans and offers, organisation and workspace management, and the usage dashboard. It shares the brand's dark-first visual system, and the capture above is that theme. The console itself never handles credentials — login and signup live on their own surface at :5000.

---

Why General Bots

Most "AI agent" tooling stops at a chat window. General Bots is the platform underneath it: an orchestration layer that connects frontier or local LLMs to real business systems, real documents and real workflows.

• Multi-agent, not multi-chat. Orchestrate several bots with distinct personalities, tools and knowledge bases from one dashboard.
• Agentic AI workflows. Autonomous task execution that plans, calls tools and reports back — in chat or over WhatsApp.
• Sovereign by default. Runs entirely offline or air-gapped. No data leaves your network unless you route it out.
• Model-agnostic. DeepSeek, Qwen, GLM, Kimi, MiniMax, Yi, Step, Doubao, OpenAI, Anthropic — or any OpenAI-compatible endpoint, including a local llama.cpp server.
• Advanced RAG. Agentic RAG, Graph RAG, persistent memory and multi-modal retrieval over PDFs, Word, Excel and web pages.
• Low-code by design. Bot behaviour is defined in BASIC dialogs and documents, so domain experts can contribute without a computer science degree.

You write this, and the bot is live:

' start.bas
USE KB "product-manual"
USE TOOL "create_ticket"

ADD_SUGGESTION "Check my order"
ADD_SUGGESTION "Open a support ticket"

TALK "Hi! I can check orders or open a ticket for you."

---

Applications

Every application is a self-contained module that can be deployed alone or as part of the whole platform. This repository ships 80 suite applications and 113 backend crates; the catalogue below is the platform map, and every entry has its own icon in .github/svg/.

	Application	What it does
<img src=".github/svg/server.svg" width="32">	Server<br><sub>Core Platform</sub>	Web server, WebSocket messaging, REST API and request routing. Serves both the API and the web interface.
<img src=".github/svg/auth.svg" width="32">	Auth / Identity<br><sub>Core Platform</sub>	OAuth 2.0, OpenID Connect, JWT validation and session management, with role-based access control on every endpoint. SSO-ready.
<img src=".github/svg/database.svg" width="32">	Shared / Database<br><sub>Core Platform</sub>	PostgreSQL with managed schema definitions, shared models and common utilities used across every application.
<img src=".github/svg/ai-engine.svg" width="32">	AI Engine<br><sub>Core Platform</sub>	LLM provider orchestration across DeepSeek, Qwen, GLM, Kimi, MiniMax, Yi or any OpenAI-compatible API. Automatic failover, token counting, streaming and cost tracking.
<img src=".github/svg/drive.svg" width="32">	Drive / Storage<br><sub>Core Platform</sub>	S3-compatible object storage with upload, download, versioning and automatic indexing for search and RAG. Works with MinIO, AWS S3 and Wasabi.
<img src=".github/svg/dashboards.svg" width="32">	Dashboards / Analytics<br><sub>Core Platform</sub>	Real-time dashboards covering system health, business KPIs and custom visualisations. Exportable and embeddable.
<img src=".github/svg/ai-search.svg" width="32">	AI Search<br><sub>Capabilities</sub>	Retrieval-augmented generation over PDFs, Word and Excel with sub-second semantic retrieval and cited answers.
<img src=".github/svg/bot-factory.svg" width="32">	Bot Factory<br><sub>Capabilities</sub>	Rapid prototyping and multi-bot orchestration. Run many bots with distinct personalities from one dashboard.
<img src=".github/svg/broadcast.svg" width="32">	Broadcast<br><sub>Capabilities</sub>	Omnichannel outbound messaging with AI-driven personalisation across WhatsApp, Telegram and SMS.
<img src=".github/svg/content-gen.svg" width="32">	Content Generation<br><sub>Capabilities</sub>	Generate on-brand, SEO-optimised content in a consistent brand voice.
<img src=".github/svg/apis-in-basic.svg" width="32">	APIs in BASIC<br><sub>Capabilities</sub>	Build REST endpoints using simplified BASIC syntax, for legacy integration and rapid delivery.
<img src=".github/svg/llm-tools.svg" width="32">	LLM Tools<br><sub>Capabilities</sub>	Give the model real capabilities: web search, calculation and custom API calls.
<img src=".github/svg/talk-to-data.svg" width="32">	Talk to Data<br><sub>Capabilities</sub>	Query SQL databases, Excel files and CSVs in plain language.
<img src=".github/svg/training.svg" width="32">	Training<br><sub>Capabilities</sub>	Ingest institutional knowledge from Word, Excel and PDF documents with no coding.
<img src=".github/svg/advanced-rag.svg" width="32">	Advanced RAG<br><sub>Capabilities</sub>	Agentic RAG, Graph RAG, persistent memory and multi-modal retrieval over the knowledge base.
<img src=".github/svg/calendar.svg" width="32">	Calendar<br><sub>Business & Productivity</sub>	CalDAV integration with event creation, conflict detection and automated reminder workflows. Syncs with Google, Outlook and Apple Calendar.
<img src=".github/svg/email.svg" width="32">	Email<br><sub>Business & Productivity</sub>	IMAP/SMTP integration with automatic templating, attachment handling and trigger-based workflows across inbox, starred, sent and scheduled folders.
<img src=".github/svg/meet.svg" width="32">	Meet / Video<br><sub>Business & Productivity</sub>	Video conferencing with screen sharing, recording, transcription and auto-generated meeting notes.
<img src=".github/svg/documents.svg" width="32">	Documents, Sheets & Slides<br><sub>Business & Productivity</sub>	Office-compatible document processing. Read and generate Word, Excel and PowerPoint files from templates.
<img src=".github/svg/channels.svg" width="32">	WhatsApp & Teams<br><sub>Business & Productivity</sub>	WhatsApp Business API and the MS Teams bot framework, with template messages, proactive notifications and rich media.
<img src=".github/svg/crm.svg" width="32">	People / CRM<br><sub>Business & Productivity</sub>	Contact management with CRM-style relationship tracking, tagging, deal pipelines and automated follow-up reminders.
<img src=".github/svg/knowledge-base.svg" width="32">	Knowledge Base<br><sub>AI & Intelligence</sub>	Automatic document ingestion with chunking, embedding and semantic search. PDFs, Word files and web pages all become queryable.
<img src=".github/svg/web-automation.svg" width="32">	Web Automation<br><sub>AI & Intelligence</sub>	Headless browser automation. Scrape sites, fill forms, capture screenshots and trigger workflows when a page changes.
<img src=".github/svg/search.svg" width="32">	Search<br><sub>AI & Intelligence</sub>	Full-text and semantic search across everything indexed, combining keyword and vector matching with faceted filtering.
<img src=".github/svg/security.svg" width="32">	Security<br><sub>Operations</sub>	Encryption, threat detection, audit logging and compliance reporting, built to LGPD, GDPR and HIPAA expectations.
<img src=".github/svg/monitoring.svg" width="32">	Monitoring<br><sub>Operations</sub>	System health monitoring for CPU, memory, disk and network, with alert thresholds, escalation and uptime tracking.
<img src=".github/svg/analytics.svg" width="32">	Analytics<br><sub>Operations</sub>	Event tracking, funnel analysis and conversion metrics across every channel.
<img src=".github/svg/rbac.svg" width="32">	RBAC & Multi-Tenancy<br><sub>Enterprise</sub>	Fine-grained role-based access control and multi-tenant workspaces with complete data isolation between organisations.
<img src=".github/svg/on-premise.svg" width="32">	On-Premise Deployment<br><sub>Enterprise</sub>	Runs entirely inside your own infrastructure with no cloud dependency and no data leaving the network. Air-gapped deployments supported.
<img src=".github/svg/compliance.svg" width="32">	Compliance (LGPD, GDPR)<br><sub>Enterprise</sub>	Data subject requests, right to erasure, audit trails, retention policies and anonymisation tooling.

Beyond the in-browser suite, the same agent layer drives WhatsApp Business, MS Teams, Telegram and email.

---

Architecture

Two Rust services, one workspace, thirteen platform services behind them.

<a href=".github/svg/diagram-platform.svg"><img src=".github/svg/diagram-platform.svg" alt="Platform architecture: clients and channels reach Caddy, which routes to botui on three ports and to botserver, whose message pipeline runs channel_entry to consent gate to start.bas to knowledge base retrieval to the API catalog to tool execution and out to the client, over the BASIC engine, drive compiler and app registry, with the AI layer, data services and drive tenancy model below" width="1500"></a>

The full picture, top to bottom. Clients and channels reach Caddy, which routes to botui (three ports, one binary) and botserver (8080, HTTP and WebSocket). Inside botserver a message runs channel_entry → consent_gate → start.bas → kb/RAG → api_catalog → tool_exec → sink, over the BASIC (Rhai) engine, the drive compiler and the app registry that gives the model a UI automation surface. Below that sit the AI layer — botllm routing across Claude, Bedrock, Vertex, GLM, Kimi, Kiro or a local llama.cpp — the data services (PostgreSQL, Vault, Valkey, MinIO, Zitadel, Qdrant, Stalwart, LiveKit) and the drive tenancy model ({org}.gborg → {workspace}.gbai → {bot}) that drive_monitors discovers from object storage at runtime.

botserver is the platform core: 113 domain crates, one per business domain (botcrm, botcalendar, botdrive, botlearn, botcloud, …). Business logic belongs there, not in the API surface.

botui serves the front end on three ports from a single binary: the desktop suite on 3000, the cloud/SaaS pages on 4000, and login/signup on 5000.

A message flows as: WebSocket → session → start.bas (once per session) → knowledge-base injection → LLM or direct tool execution → streamed response. Message type 6 skips the model entirely and runs the compiled .ast through Rhai.

The long-form version — every module, the two security crates, the RAG modes — is in BotBook → Architecture.

Ports

Port	Service	What it serves
3000	botui (suite)	Desktop suite and the 80 applications
4000	botui (cloud)	Store, plans, dashboard, organizations
5000	botui (login)	Login and signup — the only auth surface
8080	botserver	REST API and WebSocket

---

Getting Started

Download the desktop app (Linux x86_64)

Product releases use vMAJOR.MINOR.PATCH tags. The latest links always point at the newest product release, which carries the desktop installer and its checksums:

curl -fL -O https://github.com/generalbots/generalbots/releases/latest/download/generalbots-linux-x86_64.tar.gz
curl -fL -O https://github.com/generalbots/generalbots/releases/latest/download/SHA256SUMS-linux
sha256sum -c <(grep ' generalbots-linux-x86_64.tar.gz' SHA256SUMS-linux)
tar -xzf generalbots-linux-x86_64.tar.gz
cd generalbots-*-linux-x86_64
./install.sh        # per-user install, no root required
general-bots        # first run opens the setup wizard

Windows and macOS builds are published as -windows and -macos pre-releases so they never take latest; component builds (alm-*, pythonbox-*, drive-bin-*) are pre-releases too. See desktop/linux/README.txt for the full platform matrix.

Requirements

• Rust — a recent stable toolchain from rustup.rs (edition 2021)
• Git
• mold (optional, faster linking) — sudo apt-get install mold

Run it

git clone https://github.com/generalbots/generalbots
cd generalbots
./restart.sh

restart.sh stops anything already running, builds botserver and botui in order, and starts both. BotServer then provisions its own stack — PostgreSQL, Vault, MinIO, Valkey, Zitadel, Qdrant and a local llama.cpp server — and reads every credential from Vault. No global database or Redis install is needed or wanted.

Once it is up:

• Suite → http://localhost:3000
• Cloud → http://localhost:4000
• Login → http://localhost:5000/login
• API → http://localhost:8080/health

First boot downloads the stack and models, so give it a few minutes. Logs go to botserver.log and botui.log:

tail -f botserver.log botui.log

Run just the API

cd botserver
cargo run -- --noconsole

---

Building Bots

Bots are directories, not code. A bot lives in Drive as {bot}.gbai/ and is picked up automatically:

mybot.gbai/
├── mybot.gbdialog/     # BASIC scripts: start.bas, tables.bas, {tool}.bas
├── mybot.gbkb/         # documents to index for retrieval
├── mybot.gbot/         # bot configuration
└── mybot.gbdrive/      # generated files and reports

Four keywords cover most of it:

USE KB "manual"          ' index documents and retrieve from them
USE TOOL "create_ticket" ' expose a tool to the LLM
TALK "How can I help?"   ' reply to the user
CALL "other_script"      ' run another dialog

See the BotBook for the full keyword reference and worked examples.

---

Repository Layout

Directory	What it is
botserver/	Platform core — API, agents, BASIC engine, 113 crates
botui/	Web front end — suite, cloud and login servers
botapp/	Tauri desktop wrapper
botlib/	Shared types and utilities
botbook/	Documentation source (mdBook)
bottemplates/	Ready-made bot templates
bottest/	Cross-crate integration tests
botdevice/	Device and IoT integrations
botplugin/	Browser extension
botmodels/	Data-model tooling

This is a single repository — there are no git submodules. Push to origin for the public mirror; pushing to alm triggers the CI/CD pipeline that builds and deploys, so confirm first.

---

Contributing

Read AGENTS.md before opening a pull request. It carries the coding rules, security directives and testing workflow the project holds to: no unwrap()/expect() in production paths, no #[allow()] suppressions, no CDN assets, and files kept under 450 lines.

Before adding a .md file, search botbook/ for existing documentation.

---

License

MIT License — see LICENSE. Each subproject carries its own copy (botserver/LICENSE, botui/LICENSE, botlib/LICENSE.txt, …).

General Bots has been developed as open source since 2017.

<p align="center">_{Built in Rust · 536,000+ lines · <a href="https://generalbots.org">generalbots.org</a>}</p>