WeKnora MCP Server
Enables interaction with the WeKnora knowledge management API, including tenant, knowledge base, knowledge, model, session, chat, and chunk management.
README
WeKnora MCP Server
这是一个 Model Context Protocol (MCP) 服务器,提供对 WeKnora 知识管理 API 的访问。
快速开始
1. 安装依赖
pip install -r requirements.txt
2. 配置环境变量
# Linux/macOS
export WEKNORA_BASE_URL="http://localhost:8080/api/v1"
export WEKNORA_API_KEY="your_api_key_here"
# Windows PowerShell
$env:WEKNORA_BASE_URL="http://localhost:8080/api/v1"
$env:WEKNORA_API_KEY="your_api_key_here"
# Windows CMD
set WEKNORA_BASE_URL=http://localhost:8080/api/v1
set WEKNORA_API_KEY=your_api_key_here
3. 运行服务器
推荐方式 - 使用主入口点:
python main.py
其他运行方式:
# 使用原始启动脚本
python run_server.py
# 使用便捷脚本
python run.py
# 直接运行服务器模块
python weknora_mcp_server.py
# 作为 Python 模块运行
python -m weknora_mcp_server
4. 命令行选项
python main.py --help # 显示帮助信息
python main.py --check-only # 仅检查环境配置
python main.py --verbose # 启用详细日志
python main.py --version # 显示版本信息
安装为 Python 包
开发模式安装
pip install -e .
安装后可以使用命令行工具:
weknora-mcp-server
# 或
weknora-server
生产模式安装
pip install .
构建分发包
# 使用 setuptools
python setup.py sdist bdist_wheel
# 使用现代构建工具
pip install build
python -m build
测试模组
运行测试脚本验证模组是否正常工作:
python test_module.py
功能特性
该 MCP 服务器提供以下工具:
租户管理
create_tenant- 创建新租户list_tenants- 列出所有租户
知识库管理
create_knowledge_base- 创建知识库list_knowledge_bases- 列出知识库get_knowledge_base- 获取知识库详情delete_knowledge_base- 删除知识库hybrid_search- 混合搜索
知识管理
create_knowledge_from_url- 从 URL 创建知识list_knowledge- 列出知识get_knowledge- 获取知识详情delete_knowledge- 删除知识
模型管理
create_model- 创建模型list_models- 列出模型get_model- 获取模型详情
会话管理
create_session- 创建聊天会话get_session- 获取会话详情list_sessions- 列出会话delete_session- 删除会话
聊天功能
chat- 发送聊天消息
块管理
list_chunks- 列出知识块delete_chunk- 删除知识块
故障排除
如果遇到导入错误,请确保:
- 已安装所有必需的依赖包
- Python 版本兼容(推荐 3.8+)
- 没有文件名冲突(避免使用
mcp.py作为文件名)
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.