GiljoAI MCP

GiljoAI MCP

A passive context server that stores product knowledge, generates structured prompts, and coordinates multi-agent workflows via the Model Context Protocol, enabling AI coding tools to share a full picture of the product.

Category
访问服务器

README

<div align="center">

<img src="docs/images/hero-card.png" alt="GiljoAI MCP" width="100%">

<br>

Context engineering platform for AI-assisted software development. <br> Define your product once. Every agent that connects gets the full picture.

<br>

Python FastAPI Vue 3 Node.js PostgreSQL License Setup MCP Conformance Backend CI Frontend CI CodeQL

<br>

Free Community Edition · Self-Hosted · Privacy First · Bring Your Own AI

Works with: Claude Code CLI · Claude.ai / Desktop · Codex CLI · ChatGPT.com · Gemini CLI · Antigravity CLI · Any MCP Client

<br>

Website · Getting Started · Documentation · User Guide

</div>

<br>

<div align="center"> <img src="docs/images/staging-view.png" alt="GiljoAI MCP staging view: your description becomes a mission, agents are assigned automatically" width="100%"> <br> <sub>The Staging view: write what you want done. GiljoAI generates the mission and assigns agents from your templates.</sub> </div>

<br>

<div align="center"> <img src="docs/images/section-what-is.png" alt="What Is GiljoAI MCP" width="100%"> </div>

GiljoAI MCP is a passive context server for AI coding tools. It stores your product knowledge, generates structured prompts, and coordinates multi-agent workflows via the Model Context Protocol (MCP). It does not write code or call any AI model. Your AI coding tool does all reasoning and coding using your own subscription.

GiljoAI sits at the intersection of product thinking and development. Whether you are a developer learning to define what you build before you build it, or a product manager turning a specification into working software, the platform gives you a structured path from vision to execution. The clearer your product definition, the more effective every agent session becomes.

Bring Your Own AI. GiljoAI works with Claude Code CLI, Claude.ai / Desktop, Codex CLI, ChatGPT.com, Gemini CLI, Antigravity CLI, or any MCP-compatible tool. Each connects with its own API key. You can run multiple tools simultaneously.

<br>

<div align="center"> <img src="docs/images/section-quick-start.png" alt="Quick Start" width="100%"> </div>

Windows (PowerShell):

irm giljo.ai/install.ps1 | iex

Linux / macOS:

curl -fsSL giljo.ai/install.sh | bash

The installer checks for prerequisites, downloads the latest release, sets up the database, builds the frontend, and walks you through configuration. When done, run python startup.py to start the server. First run opens the Setup Wizard in your browser.

<details> <summary>Manual install (advanced)</summary>

git clone https://github.com/giljoai/GiljoAI_MCP.git
cd GiljoAI_MCP
python install.py
python startup.py

Requires Python 3.12+, PostgreSQL 18+, Node.js 22+. </details>

<br>

<div align="center"> <img src="docs/images/section-six-pillars.png" alt="The Six Pillars" width="100%"> </div>

Your Tools, Your Subscription

GiljoAI never touches your AI credits. You bring your own Claude Code CLI, Claude.ai / Desktop, Codex CLI, ChatGPT.com, Gemini CLI, Antigravity CLI, or any MCP-compatible tool, each with your own subscription. GiljoAI acts as a passive MCP server: your tool connects over HTTP, reads context and coordination data, and does all the reasoning and coding itself.

Define Your Product

<div align="center"> <img src="docs/images/product-context.png" alt="Product context form with tech stack configuration" width="100%"> </div>

Create a Product to represent the software you are building. Fill in context fields: description, tech stack, architecture, testing strategy, and more. Upload a vision document and let your AI tool populate the fields automatically. Vision documents are the most impactful input you can give GiljoAI. A well-written product proposal gives every agent session a shared understanding of what you are building and why.

Projects and Missions

  1. Create a project and describe what needs to be done.
  2. Activate the project. GiljoAI assembles a bootstrap prompt from your product context, 360 Memory, and project description.
  3. Paste the prompt into your CLI tool. The orchestrator plans the mission and spawns agents.
  4. Agents report status back in real time. You monitor progress on the Jobs page.
  5. When the project completes, GiljoAI writes a 360 Memory entry. The next project inherits that accumulated context.

Skills and Agent Templates

One skill is installed on your machine during setup. Use it from your CLI without breaking flow:

Skill Claude Code Codex CLI Gemini CLI Antigravity CLI What it does
Projects and tasks /giljo $giljo /giljo $giljo Capture tasks, create or update projects, and look them up mid-session — one command routes both create and read

Agent templates install and refresh through the giljo_setup tool (choose "Agents only"), not a slash command. The Agent Template Manager in the dashboard lets you customize agent profiles with roles, expertise, and chain strategies. Templates export in the correct format for your connected platform.

360 Memory

Each completed project writes to 360 Memory automatically: what was built, key decisions, patterns discovered, and what worked. This is not a plugin; it is a core product behavior. Your next project starts with accumulated context from previous ones. You control how many memories back agents read through the context settings. Optionally enrich memory with git commit history.

Dashboard and Monitoring

<div align="center"> <img src="docs/images/implementation-view.png" alt="Implementation view showing agents with status, progress, and messages" width="100%"> </div>

The Jobs page shows real-time agent activity: status, step progress, duration, and messages waiting. A message composer lets you talk directly to the orchestrator or broadcast to the entire agent team. All messages are logged in the MCP message system for auditability.

<br>

<div align="center"> <img src="docs/images/section-edition.png" alt="Edition" width="100%"> </div>

This is the GiljoAI MCP Community Edition, free for single-user use under the Elastic License 2.0.

Community Edition (Free) SaaS Edition
Self-hosted on your machine Managed hosting
Full context assembly and agent coordination Everything in CE, plus:
6 agent templates + customization OAuth / SSO / MFA
Real-time dashboard and monitoring Team collaboration and role-based access
Unlimited projects, up to 8 active agents Billing, usage metering
No telemetry, no cloud dependency Enterprise deployment options

Multi-user use requires a commercial license.

<br>

<div align="center"> <img src="docs/images/section-tech-stack.png" alt="Tech Stack" width="100%"> </div>

Layer Technology
Backend Python 3.12+, FastAPI, SQLAlchemy 2.0 (async), Alembic
Database PostgreSQL 18 (required)
Frontend Vue 3 (Composition API), Vuetify 4, Vite
Real-time WebSocket via PostgresNotifyBroker
Auth JWT httpOnly cookies, CSRF double-submit
Protocol Model Context Protocol (MCP) over HTTP

<br>

<div align="center"> <img src="docs/images/section-architecture.png" alt="Architecture" width="100%"> </div>

Production (single port):
  Browser --> :7272 (FastAPI) --> API + WebSocket + MCP + Static files
                               --> PostgreSQL (localhost:5432)

Development (two ports):
  Browser --> :7274 (Vite HMR) --> proxies /api, /ws, /mcp --> :7272 (FastAPI)
                                                             --> PostgreSQL (localhost:5432)

Database always runs on localhost. Auth is required for all connections. Multi-tenant isolation is enforced at the database level on every query.

<br>

<div align="center"> <img src="docs/images/section-installation.png" alt="Installation Options" width="100%"> </div>

python install.py              # Production install (recommended)
python install.py --dev        # Developer install (adds pre-commit hooks, NLTK data)
python install.py --headless   # Non-interactive mode for CI/CD
python startup.py              # Auto-detect mode and start
python startup.py --dev        # Development mode with Vite hot-reload
python startup.py --setup      # Re-run the Setup Wizard
python startup.py --no-browser # Start without opening the browser
python startup.py --verbose    # Detailed logging
Mode Ports Use case
Production Single port 7272 Users running the product
Development API 7272 + Frontend 7274 Contributors making code changes

<br>

<div align="center"> <img src="docs/images/section-documentation.png" alt="Documentation" width="100%"> </div>

Document Description
User Guide Every page and feature, from code inspection
Product Overview What it is, who it is for, the Six Pillars
Getting Started Post-install walkthrough, from setup wizard to first project
Installation Guide Complete installation reference
MCP Tools Reference All 29 MCP tools with parameters and return values
Architecture System design, network topology, component overview

API docs are served at runtime: Swagger UI at /docs, ReDoc at /redoc.

<br>

<div align="center"> <img src="docs/images/section-security.png" alt="Security" width="100%"> </div>

  • JWT authentication required for all connections (no IP-based bypass)
  • bcrypt password hashing (cost factor 12), minimum 12 characters
  • 4-digit recovery PIN for self-service password reset (no email needed)
  • Database always on localhost, never exposed to the network
  • Plain HTTP by default; opt-in HTTPS (bring-your-own certificate) in Settings → Network
  • Multi-tenant isolation on every database query
  • Rate limiting on authentication endpoints

<br>

<div align="center"> <img src="docs/images/section-support.png" alt="Support" width="100%"> </div>

<br>

<div align="center">

GiljoAI MCP is built by GiljoAI.

</div>

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选