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LseKit
SequentialThinking
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"""
Sequential Thinking MCP
路径: __init__.py
原作者: 小逸 (重构自 spences10/mcp-sequentialthinking-tools)
官方仓库: https://github.com/LseKit/SequentialThinking
一个基于 FastMCP 的 AI 辅助顺序推理和思维链管理工具。
支持 20 个 MCP 工具,涵盖会话管理、质量控制、管理功能和增强功能。
主要特性:
- 9 种思维模板(科学方法、五问法、根因分析、决策矩阵等)
- 启发式引擎 + LLM 引擎双模式
- SQLite 异步持久化存储(WAL 模式)
- 分支推理和洞察合并
- 5 维质量评估和认知偏见检测
目录结构:
- Core/: 数据模型、模板、上下文
- Engine/: 推理引擎(启发式 + LLM)
- Storage/: SQLite 异步存储
- Handlers/: MCP 工具处理器(20 个工具)
- Server/: FastMCP 服务入口
- Utils/: 日志等通用工具
使用方式:
python -m GitHubSrc
# 或
from GitHubSrc.Server.Main import mcp
mcp.run(transport="http", host="127.0.0.1", port=20010)
环境变量:
DEEPSEEK_API_KEY: LLM API 密钥(必填,否则使用启发式引擎)
ST_LLM_API_BASE: API 端点(默认 https://api.deepseek.com/v1)
ST_LLM_MODEL: 模型名称(默认 deepseek-v4-flash)
ST_LLM_TIMEOUT: 超时秒数(默认 120)
ST_DB_PATH: 数据库路径(CLI 参数 --db-path 可覆盖)
"""
__version__ = "1.2.1"
__author__ = "小逸"
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