jcode编码代理框架 是 AI Skill Hub 本期精选MCP工具之一。已获得 6.3k 颗 GitHub Star,综合评分 8.2 分,整体质量较高。我们强烈推荐将其纳入你的 AI 工具库,帮助提升工作效率。
基于MCP协议的开源编码代理工具,为Claude等LLM提供结构化编程任务执行能力。支持多种编程语言,提供CLI接口和代理编排功能。适合AI应用开发者、智能编程工具构建者和LLM集成工程师使用。
jcode编码代理框架 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。
基于MCP协议的开源编码代理工具,为Claude等LLM提供结构化编程任务执行能力。支持多种编程语言,提供CLI接口和代理编排功能。适合AI应用开发者、智能编程工具构建者和LLM集成工程师使用。
jcode编码代理框架 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/1jehuang/jcode
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"jcode------": {
"command": "npx",
"args": ["-y", "jcode"]
}
}
}
# 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 jcode编码代理框架 执行以下任务... Claude: [自动调用 jcode编码代理框架 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": {
"jcode______": {
"command": "npx",
"args": ["-y", "jcode"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
Agents dont like to commit in dirty git state with active changes. Git was clearly not built for multi-agent workflows, and git worktrees is not a good solution. Given this, I believe that is an opporunity for a new git like primitive to be born.
Build speed improvements: An incremental debug cargo build with cache enabled takes about 1 minute on my machine. The goal is 5-20 seconds. Refactors and crates seams should be able to make this happen.
---
</div>
```bash
If you prefer to configure things by editing files instead of using the login UI, jcode supports both a custom OpenAI-compatible endpoint config and MCP config files.
Many hosted services speak the standard OpenAI /v1/chat/completions API. jcode talks to them through one shared OpenAI-compatible provider, so you can use almost any such endpoint without waiting for a dedicated integration.
There are two ways to set one up:
jcode login --provider <profile-id>
# for example:
jcode login --provider openrouter
jcode login --provider deepseek
jcode login --provider opencode # OpenCode Zen
jcode login --provider moonshotai
Built-in OpenAI-compatible profile ids include: openrouter, deepseek, zai, kimi, moonshotai, opencode (OpenCode Zen), opencode-go, 302ai, baseten, cortecs, huggingface, nebius, scaleway, stackit, and firmware. Each profile only sets the endpoint and key variable; you still pick the model with /model (or --model). Run jcode login with no provider to see the interactive list.
jcode login --provider openai-compatible or the scriptable jcode provider add command described below.Useful environment overrides for these endpoints:
JCODE_STREAM_IDLE_TIMEOUT_SECS — raise the streaming idle timeout (default 180s) for slow reasoning models that think silently before emitting tokens. Also settable as [provider] stream_idle_timeout_secs in config.toml.context_window (alias context_limit) in a [[providers.<name>.models]] entry — set the context window when the endpoint has no usable /v1/models response, so jcode does not fall back to the generic 200k default.extra_body — inject non-standard top-level fields into every chat/completions request body for backends that require them. See Extra request-body fields below.For details on self-hosting, local runtimes, and the exact config file shape, see below.
For agents and scripts, the preferred path is the one-shot provider profile command. It writes a named profile to ~/.jcode/config.toml, stores secrets in jcode's private app config directory when requested, and prints exact run/validation commands:
```bash
printf '%s' "$MY_API_KEY" | jcode provider add my-api \ --base-url https://llm.example.com/v1 \ --model my-model-id \ --api-key-stdin \ --set-default \ --json
ollama pull llama3.2 jcode login --provider ollama jcode --provider ollama --model llama3.2 run 'hello'
If you want another agent to set up jcode for you, give it this prompt:
Set up jcode on this machine for me.
1. Detect the operating system, available package managers, and shell environment, then install jcode using the best matching command below instead of referring me somewhere else:
- macOS with Homebrew available:
brew tap 1jehuang/jcode
brew install jcode
- macOS or Linux via install script:
curl -fsSL https://raw.githubusercontent.com/1jehuang/jcode/master/scripts/install.sh | bash
- Windows PowerShell:
irm https://raw.githubusercontent.com/1jehuang/jcode/master/scripts/install.ps1 | iex
- From source if the above paths are not appropriate:
git clone https://github.com/1jehuang/jcode.git
cd jcode
cargo build --release
scripts/install_release.sh
- For local self-dev / refactor work on Linux x86_64, prefer:
scripts/dev_cargo.sh build --release -p jcode --bin jcode
scripts/dev_cargo.sh --print-setup
scripts/install_release.sh
2. Verify that `jcode` is on my `PATH`.
3. Launch `jcode` once in a new terminal window/session to confirm it starts successfully.
4. Before attempting any interactive login flow, assess which providers are already available non-interactively and prefer those first. Check existing local credentials, config files, CLI sessions, and environment variables such as:
- Claude: `~/.jcode/auth.json`, `~/.claude/.credentials.json`, `~/.local/share/opencode/auth.json`, `ANTHROPIC_API_KEY`
- OpenAI: `~/.jcode/openai-auth.json`, `~/.codex/auth.json`, `OPENAI_API_KEY`
- Gemini: `~/.jcode/gemini_oauth.json`, `~/.gemini/oauth_creds.json`
- GitHub Copilot: existing auth under `~/.config/github-copilot/`
- Azure OpenAI: `~/.config/jcode/azure-openai.env`, `AZURE_OPENAI_*`, or an existing `az login`
- OpenRouter: `OPENROUTER_API_KEY`
- Fireworks: `~/.config/jcode/fireworks.env`, `FIREWORKS_API_KEY`
- MiniMax: `~/.config/jcode/minimax.env`, `MINIMAX_API_KEY`
- NVIDIA NIM: `~/.config/jcode/nvidia-nim.env`, `NVIDIA_API_KEY`
- Alibaba Cloud Coding Plan: existing jcode config/env if present
5. Prefer whichever provider is already configured and verify it with `jcode auth-test --all-configured` or a provider-specific auth test when appropriate.
6. Only if no usable provider is already configured, guide me through the minimal manual step needed:
- Claude: `jcode login --provider claude`
- GitHub Copilot: `jcode login --provider copilot`
- OpenAI: `jcode login --provider openai`
- Gemini: `jcode login --provider gemini`
- Azure OpenAI: `jcode login --provider azure`
- Fireworks: `jcode login --provider fireworks`
- MiniMax: `jcode login --provider minimax`
- NVIDIA NIM: `jcode login --provider nvidia-nim`
- Alibaba Cloud Coding Plan: `jcode login --provider alibaba-coding-plan`
- OpenRouter: help me set `OPENROUTER_API_KEY`
- Anthropic direct API: help me set `ANTHROPIC_API_KEY`
7. After setup, run a simple smoke test with `jcode run "say hello"` and confirm it works.
8. If I want browser automation, also check `jcode browser status`. If browser automation is not ready, run `jcode browser setup`, verify the built-in `browser` tool works, and explain any remaining manual step.
9. Explain any manual step that still needs me, especially browser OAuth, device login, API key entry, or browser extension approval.
This is intended to be a copy-paste bootstrap prompt for jcode itself or any other coding agent.
```bash
</div>
```bash
OPENAI_COMPAT_API_KEY=your-token-here
Notes:
- `jcode login --provider openai-compatible` can create or update this for you.
- Plain `http://` is accepted for `localhost` and private LAN IPs. Public remote HTTP is still rejected.
- HTTPS endpoints work as usual.
#### MCP config files
MCP config is separate from `config.toml`.
Primary config files:
- `~/.jcode/mcp.json` for global MCP servers
- `.jcode/mcp.json` for project-local MCP servers
Claude Code compatibility:
- `~/.claude.json` (Claude Code's user config): top-level `mcpServers`, plus per-project servers under `projects.<abs_path>.mcpServers` for the current directory
- `.mcp.json` at the repo root (Claude Code's project config)
- `.claude/mcp.json` (legacy fallback)
Both the canonical `mcpServers` key and jcode's historical `servers` key are accepted. jcode currently supports stdio (command-based) servers only; HTTP/SSE entries (`"type": "http"`/`"sse"`) are recognized and skipped with a log line.
Example MCP config:
json { "mcpServers": { "filesystem": { "command": "/path/to/mcp-server", "args": ["--root", "/workspace"], "env": {}, "shared": true } } }
On first run, jcode also tries to import MCP servers from `~/.claude.json` (falling back to the legacy `~/.claude/mcp.json`) and `~/.codex/config.toml` if `~/.jcode/mcp.json` does not exist yet.
For headless or SSH sessions, OAuth-style providers support `jcode login --provider <provider> --no-browser` (alias: `--headless`) so jcode prints the auth URL/QR and falls back to manual code or callback paste instead of trying to launch a local browser.
For more scriptable remote flows, `claude`, `openai`, `gemini`, and `antigravity` also support a two-step pattern:
bash
jcode login --provider google --print-auth-url --google-access-tier readonly jcode login --provider google --callback-url 'http://127.0.0.1:8456?...' ```
Pending scriptable login state is stored under ~/.jcode/pending-login/, automatically expires, and stale entries are cleaned up when new scriptable logins start or resume.
For the built-in OpenAI login flow, jcode opens a local callback on http://localhost:1455/auth/callback by default.
<img width="2877" height="1762" alt="Screenshot from 2026-04-02 14-28-51" src="https://github.com/user-attachments/assets/530684c0-9d12-4363-aa0e-1b39a0d4e1be" /> The above image is the first page of provider logins
jcode dictate ```
jcode supports interactive TUI use, non-interactive runs, persistent server/client workflows, and hotkey-friendly dictation without requiring a bundled speech-to-text stack.
<a href="https://github.com/1jehuang/jcode/releases/download/readme-assets/workflow.mp4"> <img src="https://github.com/1jehuang/jcode/releases/download/readme-assets/jcode-workflow-demonstration.webp" alt="jcode workflow demonstration" width="900"> </a>
<p><em>jcode workflow demonstration</em></p>
</div>
---
1 active session
|
10 active sessions
|
</div>
高质量MCP实现,Rust编写性能优秀。6.3k Star证实社区认可度。架构完善支持扩展,是构建智能编程系统的理想基础组件。
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。
经综合评估,jcode编码代理框架 在MCP工具赛道中表现稳健,质量优秀。如果你已有明确的使用需求,可以直接上手体验;如果还在评估阶段,建议对比同类工具后再做决策。
| 原始名称 | jcode |
| 原始描述 | 开源MCP工具:Coding Agent Harness。⭐6.3k · Rust |
| Topics | MCP协议编码代理ClaudeRustLLM工具 |
| GitHub | https://github.com/1jehuang/jcode |
| License | MIT |
| 语言 | Rust |
收录时间:2026-05-18 · 更新时间:2026-05-19 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型,复制安装指令后粘贴到对应客户端