fix: remove hardcoded paths from MCP server and documentation

docs/claude-code-integration.md

@@ -1,150 +0,0 @@
-# Claude Code x LEANN 集成指南
-
-## ✅ 现状：已经可以工作！
-
-好消息：LEANN CLI已经完全可以在Claude Code中使用，无需任何修改！
-
-## 🚀 立即开始
-
-### 1. 激活环境
-```bash
-# 在LEANN项目目录下
-source .venv/bin/activate.fish  # fish shell
-# 或
-source .venv/bin/activate       # bash shell
-```
-
-### 2. 基本命令
-
-#### 查看现有索引
-```bash
-leann list
-```
-
-#### 搜索文档
-```bash
-leann search my-docs "machine learning" --recompute-embeddings
-```
-
-#### 问答对话
-```bash
-echo "What is machine learning?" | leann ask my-docs --llm ollama --model qwen3:8b --recompute-embeddings
-```
-
-#### 构建新索引
-```bash
-leann build project-docs --docs ./src --recompute-embeddings
-```
-
-## 💡 Claude Code 使用技巧
-
-### 在Claude Code中直接使用
-
-1. **激活环境**：
-   ```bash
-   cd /Users/andyl/Projects/LEANN-RAG
-   source .venv/bin/activate.fish
-   ```
-
-2. **搜索代码库**：
-   ```bash
-   leann search my-docs "authentication patterns" --recompute-embeddings --top-k 10
-   ```
-
-3. **智能问答**：
-   ```bash
-   echo "How does the authentication system work?" | leann ask my-docs --llm ollama --model qwen3:8b --recompute-embeddings
-   ```
-
-### 批量操作示例
-
-```bash
-# 构建项目文档索引
-leann build project-docs --docs ./docs --force
-
-# 搜索多个关键词
-leann search project-docs "API authentication" --recompute-embeddings
-leann search project-docs "database schema" --recompute-embeddings
-leann search project-docs "deployment guide" --recompute-embeddings
-
-# 问答模式
-echo "What are the API endpoints?" | leann ask project-docs --recompute-embeddings
-```
-
-## 🎯 Claude 可以立即执行的工作流
-
-### 代码分析工作流
-```bash
-# 1. 构建代码库索引
-leann build codebase --docs ./src --backend hnsw --recompute-embeddings
-
-# 2. 分析架构
-echo "What is the overall architecture?" | leann ask codebase --recompute-embeddings
-
-# 3. 查找特定功能
-leann search codebase "user authentication" --recompute-embeddings --top-k 5
-
-# 4. 理解实现细节
-echo "How is user authentication implemented?" | leann ask codebase --recompute-embeddings
-```
-
-### 文档理解工作流
-```bash
-# 1. 索引项目文档
-leann build docs --docs ./docs --recompute-embeddings
-
-# 2. 快速查找信息
-leann search docs "installation requirements" --recompute-embeddings
-
-# 3. 获取详细说明
-echo "What are the system requirements?" | leann ask docs --recompute-embeddings
-```
-
-## ⚠️ 重要提示
-
-1. **必须使用 `--recompute-embeddings`** - 这是关键参数，不加会报错
-2. **需要先激活虚拟环境** - 确保有LEANN的Python环境
-3. **Ollama需要预先安装** - ask功能需要本地LLM
-
-## 🔥 立即可用的Claude提示词
-
-```
-Help me analyze this codebase using LEANN:
-
-1. First, activate the environment:
-   cd /Users/andyl/Projects/LEANN-RAG && source .venv/bin/activate.fish
-
-2. Build an index of the source code:
-   leann build codebase --docs ./src --recompute-embeddings
-
-3. Search for authentication patterns:
-   leann search codebase "authentication middleware" --recompute-embeddings --top-k 10
-
-4. Ask about the authentication system:
-   echo "How does user authentication work in this codebase?" | leann ask codebase --recompute-embeddings
-
-Please execute these commands and help me understand the code structure.
-```
-
-## 📈 下一步改进计划
-
-虽然现在已经可以用，但还可以进一步优化：
-
-1. **简化命令** - 默认启用recompute-embeddings
-2. **配置文件** - 避免重复输入参数
-3. **状态管理** - 自动检测环境和索引
-4. **输出格式** - 更适合Claude解析的格式
-
-但这些都是锦上添花，现在就能用起来！
-
-## 🎉 总结
-
-**LEANN现在就可以在Claude Code中完美工作！**
-
-- ✅ 搜索功能正常
-- ✅ RAG问答功能正常
-- ✅ 索引构建功能正常
-- ✅ 支持多种数据源
-- ✅ 支持本地LLM
-
-只需要记住加上 `--recompute-embeddings` 参数就行！

packages/leann-core/src/leann/mcp.py

@@ -1,7 +1,6 @@
 #!/usr/bin/env python3
 
 import json
-import os
 import subprocess
 import sys
 
@@ -62,10 +61,6 @@ def handle_request(request):
         tool_name = request["params"]["name"]
         args = request["params"].get("arguments", {})
 
-        # Set working directory and environment
-        env = os.environ.copy()
-        cwd = "/Users/andyl/Projects/LEANN-RAG"
-
         try:
             if tool_name == "leann_search":
                 cmd = [
@@ -76,18 +71,14 @@ def handle_request(request):
                     "--recompute-embeddings",
                     f"--top-k={args.get('top_k', 5)}",
                 ]
-                result = subprocess.run(cmd, capture_output=True, text=True, cwd=cwd, env=env)
+                result = subprocess.run(cmd, capture_output=True, text=True)
 
             elif tool_name == "leann_ask":
                 cmd = f'echo "{args["question"]}" | leann ask {args["index_name"]} --recompute-embeddings --llm ollama --model qwen3:8b'
-                result = subprocess.run(
+                result = subprocess.run(cmd, shell=True, capture_output=True, text=True)
-                    cmd, shell=True, capture_output=True, text=True, cwd=cwd, env=env
-                )
 
             elif tool_name == "leann_list":
-                result = subprocess.run(
+                result = subprocess.run(["leann", "list"], capture_output=True, text=True)
-                    ["leann", "list"], capture_output=True, text=True, cwd=cwd, env=env
-                )
 
             return {
                 "jsonrpc": "2.0",