How do I use SAG MCP Server?

1. Click on "Deploy Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@SAG MCP Server search my knowledge base for 'cancer research' papers" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

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SAG MCP Server

by guazixiong

Overview Schema Source Related Servers Discussions Admin

Python

Remote

SAG MCP Server

Python 3.10+ License: MIT MCP

English | 中文

Full read/write MCP server for SAG knowledge base. Exposes 18 tools over Streamable HTTP transport — compatible with Claude Desktop, Cursor, VS Code, and any MCP client.

Features

18 tools: source/document CRUD, semantic search, knowledge graph queries, model config
Streamable HTTP: connect from any MCP client without local dependencies
Bearer auth: JWT token authentication built-in
Zero config: works with a running SAG instance out of the box

Related MCP server: MCP RAG Server

Quick Start

1. Prerequisites

A running SAG instance (Docker or native). See SAG deployment guide.

2. Install

pip install sag-mcp-server

Or from source:

git clone https://github.com/Zleap-AI/sag-mcp-server.git
cd sag-mcp-server
pip install -e .

3. Run

HTTP mode (recommended):

export SAG_API_URL=http://your-sag-host:9002
sag-mcp-server http 9003

stdio mode (for local integration):

sag-mcp-server stdio

4. Connect from Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "sag": {
      "type": "http",
      "url": "http://your-sag-host:9003/mcp/",
      "headers": {
        "Authorization": "Bearer <your-jwt-token>"
      }
    }
  }
}

Get a token:

curl -s -X POST http://your-sag-host:9002/api/v1/auth/login \
  -H 'Content-Type: application/json' -d '{"name":"Admin"}' \
  | python3 -c "import sys,json;print(json.load(sys.stdin)['access_token'])"

Tools

Category	Tool	Description
Sources	`list_sources`	List all knowledge base sources
	`create_source`	Create a new source
	`delete_source`	Delete a source and all its data
Documents	`list_documents`	List documents in a source
	`upload_document`	Upload a local file (auto-parses + extracts)
	`ingest_text`	Write text directly (no file needed)
	`reprocess_document`	Re-process a document
	`pause_document`	Pause processing
	`resume_document`	Resume processing
	`delete_document`	Delete a document
Retrieval	`search`	Semantic search with LLM summary
	`get_entity`	Query knowledge graph entity
	`outline`	Get document outline
	`grep`	Keyword/regex search
	`read_document`	Read full document text
Config	`get_model_config`	View model configuration
	`update_model_config`	Update model settings
	`test_model_config`	Test model connectivity

Configuration

All configuration via environment variables:

Variable	Default	Description
`SAG_API_URL`	`http://localhost:9002`	SAG API base URL
`SAG_TOKEN`	(empty = auto-login)	JWT Bearer token
`SAG_LOGIN_NAME`	`Admin`	Login username (when token is empty)
`SAG_MCP_PORT`	`9003`	HTTP server port

Client Configuration

Claude Desktop

{
  "mcpServers": {
    "sag": {
      "type": "http",
      "url": "http://your-sag-host:9003/mcp/",
      "headers": { "Authorization": "Bearer <token>" }
    }
  }
}

Cursor

~/.cursor/mcp.json:

{
  "mcpServers": {
    "sag": {
      "type": "http",
      "url": "http://your-sag-host:9003/mcp/",
      "headers": { "Authorization": "Bearer <token>" }
    }
  }
}

Dify

Type: Streamable HTTP
URL: http://your-sag-host:9003/mcp/
Header: Authorization: Bearer <token>

Docker

Run as a container alongside SAG:

# docker-compose.yml addition
services:
  mcp:
    build: .
    environment:
      SAG_API_URL: http://api:8000
      SAG_SECRET_KEY: ${SAG_SECRET_KEY}
    ports:
      - "9003:9003"
    command: ["sag-mcp-server", "http", "9003"]
    depends_on:
      api:
        condition: service_healthy

Development

git clone https://github.com/Zleap-AI/sag-mcp-server.git
cd sag-mcp-server
pip install -e ".[dev]"

# Run tests
pytest

# Lint
ruff check src/

API Compatibility

Requires SAG v0.7.x+ with the following endpoints:

POST /api/v1/auth/login — JWT authentication
GET/POST/DELETE /api/v1/sources — Source CRUD
GET/POST/DELETE /api/v1/sources/{id}/documents — Document CRUD
POST /api/v1/search — Semantic search
GET /api/v1/system/model-config — Model configuration

License

MIT License. See LICENSE for details.

中文文档

English | 中文

基于 SAG 知识库的读写 MCP Server。通过 Streamable HTTP 暴露 18 个工具，兼容 Claude Desktop、Cursor、VS Code 及所有 MCP 客户端。

特性

18 个工具：信源/文档增删改查、语义检索、知识图谱查询、模型配置
Streamable HTTP：无需本地安装任何依赖，客户端通过 HTTP 直连
Bearer 鉴权：内置 JWT token 认证
零配置：与运行中的 SAG 实例直接配合使用

快速开始

1. 前提条件

运行中的 SAG 实例（Docker 或原生部署）。参见 SAG 部署指南。

2. 安装

pip install sag-mcp-server

或从源码安装：

git clone https://github.com/Zleap-AI/sag-mcp-server.git
cd sag-mcp-server
pip install -e .

3. 启动

HTTP 模式（推荐）：

export SAG_API_URL=http://your-sag-host:9002
sag-mcp-server http 9003

stdio 模式（本地集成）：

sag-mcp-server stdio

4. 连接 Claude Desktop

编辑 claude_desktop_config.json：

{
  "mcpServers": {
    "sag": {
      "type": "http",
      "url": "http://your-sag-host:9003/mcp/",
      "headers": {
        "Authorization": "Bearer <your-jwt-token>"
      }
    }
  }
}

获取 token：

curl -s -X POST http://your-sag-host:9002/api/v1/auth/login \
  -H 'Content-Type: application/json' -d '{"name":"Admin"}' \
  | python3 -c "import sys,json;print(json.load(sys.stdin)['access_token'])"

工具清单

类别	工具	说明
信源	`list_sources`	列出所有知识库信源
	`create_source`	创建新信源
	`delete_source`	删除信源及全部数据
文档	`list_documents`	列出信源下文档
	`upload_document`	上传本地文件（自动解析+抽取）
	`ingest_text`	直接写入文本（无需文件）
	`reprocess_document`	重新处理文档
	`pause_document`	暂停处理
	`resume_document`	恢复处理
	`delete_document`	删除文档
检索	`search`	语义检索（含 LLM 摘要）
	`get_entity`	查询知识图谱实体
	`outline`	获取文档大纲
	`grep`	关键词/正则检索
	`read_document`	读取文档全文
模型	`get_model_config`	查看模型配置
	`update_model_config`	更新模型设置
	`test_model_config`	测试模型连通性

配置说明

所有配置通过环境变量：

变量	默认值	说明
`SAG_API_URL`	`http://localhost:9002`	SAG API 地址
`SAG_TOKEN`	（空=自动登录）	JWT Bearer token
`SAG_LOGIN_NAME`	`Admin`	登录用户名（token 为空时生效）
`SAG_MCP_PORT`	`9003`	HTTP 服务端口

客户端配置

Claude Desktop

{
  "mcpServers": {
    "sag": {
      "type": "http",
      "url": "http://your-sag-host:9003/mcp/",
      "headers": { "Authorization": "Bearer <token>" }
    }
  }
}

Cursor

~/.cursor/mcp.json：

{
  "mcpServers": {
    "sag": {
      "type": "http",
      "url": "http://your-sag-host:9003/mcp/",
      "headers": { "Authorization": "Bearer <token>" }
    }
  }
}

Dify

类型：Streamable HTTP
URL：http://your-sag-host:9003/mcp/
请求头：Authorization: Bearer <token>

Docker 部署

与 SAG 一起以容器方式运行：

# 添加到 docker-compose.yml
services:
  mcp:
    build: .
    environment:
      SAG_API_URL: http://api:8000
      SAG_SECRET_KEY: ${SAG_SECRET_KEY}
    ports:
      - "9003:9003"
    command: ["sag-mcp-server", "http", "9003"]
    depends_on:
      api:
        condition: service_healthy

开发指南

git clone https://github.com/Zleap-AI/sag-mcp-server.git
cd sag-mcp-server
pip install -e ".[dev]"

# 运行测试
pytest

# 代码检查
ruff check src/

API 兼容性

需要 SAG v0.7.x+，支持以下接口：

POST /api/v1/auth/login — JWT 认证
GET/POST/DELETE /api/v1/sources — 信源增删改查
GET/POST/DELETE /api/v1/sources/{id}/documents — 文档增删改查
POST /api/v1/search — 语义检索
GET /api/v1/system/model-config — 模型配置

许可证

MIT License。详见 LICENSE。

This server cannot be deployed

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Maintenance

ActivityMaintained

ResponsivenessNo issues

Resources

GitHub Repository

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SAG MCP Server

Features

Quick Start

1. Prerequisites

2. Install

3. Run

4. Connect from Claude Desktop

Tools

Configuration

Client Configuration

Claude Desktop

Cursor

Dify

Docker

Development

API Compatibility

License

中文文档

特性

快速开始

1. 前提条件

2. 安装

3. 启动

4. 连接 Claude Desktop

工具清单

配置说明

客户端配置

Claude Desktop

Cursor

Dify

Docker 部署

开发指南

API 兼容性

许可证

Maintenance

Resources

Related MCP Connectors

Related MCP Servers

Daniel LightRAG MCP Server

MCP RAG Server

Works With Agents MCP Server

fayna-rag-mcpofficial