经 AI Skill Hub 精选评估,代码上下文引擎 获评「强烈推荐」。这款MCP工具在功能完整性、社区活跃度和易用性方面表现出色,AI 评分 8.0 分,适合有一定技术背景的用户使用。
代码上下文引擎 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
代码上下文引擎 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/elara-labs/code-context-engine
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"-------": {
"command": "npx",
"args": ["-y", "code-context-engine"]
}
}
}
# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
# 安装后在 Claude 对话中直接使用 # 示例: 用户: 请帮我用 代码上下文引擎 执行以下任务... Claude: [自动调用 代码上下文引擎 MCP 工具处理请求] # 查看可用工具列表 # 在 Claude 中输入:"列出所有可用的 MCP 工具"
// claude_desktop_config.json 配置示例
{
"mcpServers": {
"_______": {
"command": "npx",
"args": ["-y", "code-context-engine"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
<p align="center"> <img src="https://raw.githubusercontent.com/elara-labs/code-context-engine/main/docs/logo.svg" alt="Code Context Engine" width="140"> </p>
<p align="center"> <strong>Index your codebase. AI searches instead of re-reading files.<br>94% token savings, reproducibly benchmarked.</strong> </p>
<p align="center"> <a href="https://elara-labs.github.io/code-context-engine/">Website</a> · <a href="https://elara-labs.github.io/code-context-engine/guide/">Docs</a> · <a href="https://elara-labs.github.io/code-context-engine/guide/why-cce/">Why CCE?</a> · <a href="https://elara-labs.github.io/code-context-engine/blog/benchmark-fastapi.html">Benchmark</a> · <a href="https://github.com/elara-labs/code-context-engine">GitHub</a> </p>
<br>
<p align="center"> <a href="https://pypi.org/project/code-context-engine/"><img src="https://img.shields.io/pypi/v/code-context-engine?style=flat-square&color=blue&label=PyPI" alt="PyPI"></a> <a href="https://pepy.tech/project/code-context-engine"><img src="https://img.shields.io/pepy/dt/code-context-engine?style=flat-square&label=downloads&color=blue" alt="Downloads"></a> <a href="https://github.com/elara-labs/code-context-engine/actions/workflows/ci.yml"><img src="https://img.shields.io/github/actions/workflow/status/elara-labs/code-context-engine/ci.yml?style=flat-square&label=CI" alt="CI"></a> <a href="https://registry.modelcontextprotocol.io/?q=code-context-engine"><img src="https://img.shields.io/badge/MCP_Registry-listed-brightgreen?style=flat-square" alt="MCP Registry"></a> <a href="https://opensource.org/licenses/MIT"><img src="https://img.shields.io/badge/license-MIT-yellow?style=flat-square" alt="MIT License"></a> <a href="https://github.com/elara-labs/code-context-engine"><img src="https://img.shields.io/github/stars/elara-labs/code-context-engine?style=flat-square&label=stars" alt="Stars"></a> </p>
<p align="center"> <sub>Python 3.11+ · macOS · Linux · Windows</sub> </p>
<br>
<p align="center"> <a href="#install-and-see-savings-in-60-seconds"><img src="https://img.shields.io/badge/Claude_Code-352318?style=for-the-badge&logo=anthropic&logoColor=D4A27F" alt="Claude Code"></a> <a href="#install-and-see-savings-in-60-seconds"><img src="https://img.shields.io/badge/VS_Code-007ACC?style=for-the-badge&logo=visualstudiocode&logoColor=white" alt="VS Code"></a> <a href="#install-and-see-savings-in-60-seconds"><img src="https://img.shields.io/badge/Cursor-000?style=for-the-badge" alt="Cursor"></a> <a href="#install-and-see-savings-in-60-seconds"><img src="https://img.shields.io/badge/Gemini_CLI-4285F4?style=for-the-badge&logo=google&logoColor=white" alt="Gemini CLI"></a> <a href="#install-and-see-savings-in-60-seconds"><img src="https://img.shields.io/badge/Codex_CLI-412991?style=for-the-badge" alt="Codex CLI"></a> <a href="#install-and-see-savings-in-60-seconds"><img src="https://img.shields.io/badge/OpenCode-22C55E?style=for-the-badge&logo=gnometerminal&logoColor=white" alt="OpenCode"></a> <a href="#install-and-see-savings-in-60-seconds"><img src="https://img.shields.io/badge/Tabnine-4B32C3?style=for-the-badge&logo=tabnine&logoColor=white" alt="Tabnine"></a> </p>
<p align="center"> <sub>One command. Auto-detects your editor. Zero cloud, zero config.</sub> </p>
<br>
<p align="center"> <img src="https://raw.githubusercontent.com/elara-labs/code-context-engine/main/docs/demo.gif" alt="CCE Demo" width="720"> </p>
---
| Use case | How CCE helps | |
|---|---|---|
| **💰** | **Reduce Claude Code costs** | 94% fewer input tokens per session |
| **🔒** | **Keep code private** | Everything local, no cloud indexing |
| **🔄** | **Multi-editor teams** | One index across Claude Code, Cursor, VS Code, Gemini CLI |
| **🧠** | **Cross-session memory** | Decisions and context survive restarts |
| **⚡** | **Faster responses** | Less context = faster Claude replies |
| **📊** | **Track actual savings** | Dollar amounts, not estimates |
---
One command. 30 seconds.
uvx --from "code-context-engine[local]" cce init # install + index + configure, one shot
Or if you prefer a persistent install:
uv tool install "code-context-engine[local]" # or: pipx install "code-context-engine[local]"
cd /path/to/your/project
cce init
Restart your editor. Done. Every question now hits the index instead of re-reading files.
Already have Ollama? Skip[local]and useuv tool install code-context-engineinstead. CCE auto-detects Ollama at localhost:11434 and usesnomic-embed-text.
<details> <summary><strong>System requirements</strong></summary>
Python 3.11+ and a C compiler (for tree-sitter grammars).
| Platform | Setup |
|---|---|
| **macOS** | xcode-select --install |
| **Ubuntu/Debian** | sudo apt install build-essential cmake |
| **Fedora/RHEL** | sudo dnf install gcc gcc-c++ cmake |
| **Windows** | [Visual Studio Build Tools](https://visualstudio.microsoft.com/visual-cpp-build-tools/) (C++ workload) + [CMake](https://cmake.org/download/) |
Tested on macOS, Linux, Windows with Python 3.11/3.12/3.13. </details>
cce init auto-detects your editor and writes the right config. To target a specific agent, use --agent claude, --agent codex, --agent copilot, or --agent all.
| Editor | Config written | Instructions |
|---|---|---|
| Claude Code | .mcp.json | CLAUDE.md |
| VS Code / Copilot | .vscode/mcp.json | .github/copilot-instructions.md |
| Cursor | .cursor/mcp.json | .cursorrules |
| Gemini CLI | .gemini/settings.json | GEMINI.md |
| OpenAI Codex | ~/.codex/config.toml (user-global, per-project section) | AGENTS.md |
| OpenCode | opencode.json | |
| Tabnine | .tabnine/agent/settings.json | TABNINE.md |
Multiple editors in the same project? All get configured in one command.
Codex note: Codex CLI reads MCP servers from ~/.codex/config.toml only — it has no per-project config. cce init adds one [mcp_servers.cce-<project>-<hash>] section per project so multiple projects coexist; cce uninstall removes only the section for the current project.
my-project · 38 queries · last query 5m ago
⛁ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ 88% tokens saved
Input savings 1.9M tokens $27.78
Output savings 4.8k tokens $0.36
──────────────────────────────────────────
Total saved 1.9M tokens $28.15
Breakdown:
retrieval 84% ▰▰▰▰▰▰▰▰▰▰ 1.8M $26.76 · 12 calls
chunk compression 3% ▰▱▱▱▱▱▱▱▱▱ 68.5k $1.03 · 12 calls
output compression* <1% ▰▱▱▱▱▱▱▱▱▱ 4.8k $0.36 · 12 calls
Cost estimate based on Opus pricing (input $15.0/1M, output $75.0/1M)
Supports Anthropic, OpenAI, and Google model pricing. Configure via pricing.model in ~/.cce/config.yaml.
---
Zero-config by default. Override what you need in ~/.cce/config.yaml or .context-engine.yaml:
compression:
level: standard # minimal | standard | full
output: standard # off | lite | standard | max
ollama_url: http://localhost:11434 # point at a remote Ollama if desired
retrieval:
top_k: 20
confidence_threshold: 0.5
pricing:
model: opus # opus | sonnet | haiku | gpt-4o | gemini-2.5-pro | ...
# input: 15.0 # override $/1M input tokens
# output: 75.0 # override $/1M output tokens
Remote Ollama: If you run Ollama on another machine in your network, set compression.ollama_url (e.g. http://nas.local:11434) or export CCE_OLLAMA_URL — the env var wins. CCE probes the endpoint and falls back to truncation-only compression when it's unreachable, so a flaky link won't break indexing.
---
We benchmarked CCE against FastAPI (53 source files, 180K tokens) with 20 real coding questions. No cherry-picking, no synthetic queries.
Methodology: For each query, "without CCE" means reading the full content of every file the query touches. "With CCE" means the relevant chunks after compression.
Important baseline note: The 94% number is measured against full-file reads, not against what Claude Code actually does. In practice, Claude Code already uses grep, partial file reads, and targeted tools, so the real-world savings compared to normal Claude Code behavior will be lower than 94%. We use full-file as the baseline because it's reproducible and deterministic (no agent behavior variability). The benchmark measures CCE's retrieval efficiency, not a head-to-head comparison with Claude Code's built-in exploration.
| Metric | Result |
|---|---|
| **Retrieval savings** | **94%** (83,681 → 4,927 tokens/query) |
| Compression (additional, on retrieved chunks) | 89% (4,927 → 523 tokens/query) |
| Recall@10 (found the right files) | 0.90 |
| Latency p50 | 0.4ms |
| Queries tested | 20 |
cce init # Index + install hooks + register MCP
cce # Status banner
cce savings # Token savings with dollar estimates
cce savings --all # All projects
cce dashboard # Web dashboard with live charts
cce search "auth flow" # Test a query
cce status # Index health + config
cce services # Ollama + dashboard + MCP status
cce commands add-rule '...' # Project rules for Claude
cce uninstall # Clean removal of all CCE artifacts
Run cce list for the full command reference.
---
高效的代码索引和搜索工具
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。
AI Skill Hub 点评:代码上下文引擎 的核心功能完整,质量优秀。对于Claude Desktop / Claude Code 用户来说,这是一个值得纳入个人工具库的选择。建议先在非生产环境试用,再逐步推广。
| 原始名称 | code-context-engine |
| Topics | ai-codingcode-indexingcodex |
| GitHub | https://github.com/elara-labs/code-context-engine |
| License | MIT |
| 语言 | Python |
收录时间:2026-07-03 · 更新时间:2026-07-03 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。
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