AI Skill Hub 推荐使用:Kocoro 是一款优质的MCP工具。AI 综合评分 7.5 分,在同类工具中表现稳健。如果你正在寻找可靠的MCP工具解决方案,这是一个值得深入了解的选择。
Kocoro 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。
Kocoro 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/Kocoro-lab/Kocoro
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"kocoro": {
"command": "npx",
"args": ["-y", "kocoro"]
}
}
}
# 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 Kocoro 执行以下任务... Claude: [自动调用 Kocoro 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": {
"kocoro": {
"command": "npx",
"args": ["-y", "kocoro"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
An AI cowork agent that lives on your Mac.
Kocoro runs AI agents locally with full computer access — files, apps, browser, terminal, screen — and connects to your team's Slack / LINE / Feishu / Telegram channels via Shannon Cloud. Named agents with their own memory and tools, MCP-native, daemon-driven. The shan CLI is the runtime; Kocoro Desktop is the recommended way to use it.
memory_recall lets the agent look up facts learned from prior sessions before asking the user. Structured memory runs as a local sidecar over a Unix socket; the daemon manages spawn, readiness, restart, and bundle pull.
Opt-in — disabled by default; Kocoro Desktop's Episodic Memory toggle enables it. Three modes:
memory.provider: "disabled" (default) — no sidecar; memory_recall falls back to session search + MEMORY.mdmemory.provider: "cloud" — daemon pulls fresh memory bundles from Kocoro Cloud every 24h. Requires cloud.api_key + cloud.endpoint (overridable via memory.api_key / memory.endpoint)memory.provider: "local" — daemon runs the sidecar against bundles you build locally; no Cloud callsshan ghostty workspace writer ops-bot # open one window per agent
shan "list files on my Desktop" # filesystem MCP shan "show all tables in the database" # sqlite MCP ```
| Format | Built-in fallback | Better with |
|---|---|---|
| n/a — suggests upload so cloud renders it as a native Anthropic document block | pdftotext (brew install poppler) | |
| DOCX | unzip + XML strip (raw text) | pandoc (brew install pandoc) |
| XLSX | unzip + raw XML | xlsx2csv (pip install xlsx2csv) |
| PPTX | unzip + XML strip | pandoc (brew install pandoc) |
| HEIC / AVIF | transcoded server-side by cloud | — |
accessibility and computer tools)ghostty tool)npm (recommended) — auto-updates on every launch:
npm install -g @kocoro/kocoro
Install script — downloads the latest binary to /usr/local/bin:
curl -fsSL https://raw.githubusercontent.com/Kocoro-lab/Kocoro/main/install.sh | sh
From source — requires Go 1.25+:
git clone https://github.com/Kocoro-lab/Kocoro.git
cd Kocoro
go install .
go install places the binary in $GOPATH/bin (default ~/go/bin). Add export PATH="$HOME/go/bin:$PATH" to your shell rc if it's not already on PATH.
Verify with shan --help.
Kocoro requires a Gateway API for LLM completions and remote tools.
Shannon Cloud — get an API key from shannon.run:
```bash shan --setup
go build -o shan . # build
go test ./... # run all tests
go vet ./... # lint
shan # interactive TUI
shan "who is wayland zhang" # one-shot
shan --agent ops-bot "check prod health" # named agent
shan --setup # configure endpoint + API key
In the TUI, type / to see built-in commands:
/research deep "latest advances in AI agents"
/swarm "build a marketing plan for our launch"
/model large
/sessions # browse and resume past sessions
/search websocket reconnect # search session history
```bash
shan # interactive TUI
shan "who is wayland zhang" # one-shot (prompts for tool approval)
shan -y "query" # auto-approve all tools
shan --agent ops-bot "query" # use a named agent
shan --setup # configure endpoint + API key
shan mcp serve # MCP server over stdio
shan daemon start # channel messaging daemon
shan schedule list # local scheduled tasks
Flags: -y/--yes auto-approve; --agent named agent; --dangerously-skip-permissions skip checks in interactive mode; --setup interactive wizard.
tlm binary somewhere on $PATH (or set memory.tlm_path). cloud:
endpoint: https://api.shannon.run
api_key: <your key>
memory:
provider: cloud
shan -y "open Chrome, go to x.com, and post a tweet"
Multi-level merge — later overrides earlier:
~/.shannon/config.yaml — global.shannon/config.yaml — project.shannon/config.local.yaml — local (gitignored)Scalars override, lists merge + dedup, structs field-level merge.
Minimal ~/.shannon/config.yaml:
endpoint: https://api.shannon.run
api_key: <your key>
model_tier: medium
permissions:
allowed_commands:
- "git *"
- "make *"
See docs/config-reference.md for the full key list including agent.*, tools.*, mcp_servers, cloud, memory, sync, daemon, hooks, UI settings, etc. Run /config in the TUI to see the merged config with sources.
Per-agent overrides live in ~/.shannon/agents/<name>/_attached.yaml — including agent.model_tier so individual agents can opt into the Large (Opus) tier without changing the global default. See docs/agents-reference.md for the precedence chain.
See the memory: block in docs/config-reference.md for all keys (provider, endpoint, api_key, socket_path, bundle_root, tlm_path, bundle_pull_interval, sidecar_* timeouts).
```
Self-hosted — run the open-source Shannon Gateway locally, then shan --setup with http://localhost:8080 and an empty API key.
Ollama (local LLMs) — set provider: ollama in ~/.shannon/config.yaml. See docs/config-reference.md for the full block.
| Tool | Approval | Description |
|---|---|---|
cloud_delegate | Yes | Delegate to Shannon Cloud for remote research/swarm execution. |
publish_to_web | Yes ⚠️ | Upload to a **public** S3 URL on Shannon Cloud (50 MiB cap). Path blocklist (.env, .ssh, credentials, *.pem, …) and extension allowlist (html/md/txt/pdf/png/jpg/svg/csv/json/mp4/…). Extend allowlist via cloud.publish_allowed_extensions. Uploads are tagged kind=other server-side (Desktop UI's "All / Image / HTML / PDF / Other" filter sits alongside a separate "Session" bucket for daemon-side session shares). Files retractable via retract_published_file, but **anyone with the URL can read content until then** plus up to 5 minutes after via CDN edge cache. |
list_my_published_files | No | List the user's still-active published files. Paginated (limit default 20, max 100). Optional kind filter (session_share / report / landing_page / image / other) — omit to list every category. |
retract_published_file | Yes ⚠️ | Retract a published file by id (UUID from list, **not** the URL). Owner-only; cross-user calls return a friendly 404 (cloud conflates not-found/already-retracted/not-yours to prevent existence leaks). NOT on the high-risk auto-approval denylist — user can opt in to always_allow_tools. CDN edges may serve content for up to 5 min after success. |
generate_image | Yes ⚠️ | Generate via POST /api/v1/images/generations (gpt-image-2); returns a **public permanent** CDN URL. Args: prompt, size, quality (latency 30s→180s), n (1–10), background. Each call consumes paid quota. For charts use kocoro-generative-ui instead. |
edit_image | Yes ⚠️ | Edit via POST /api/v1/images/edits. Args: prompt + image_urls (1–4, must start with https://static.kocoro.ai/ — external URLs rejected; pipe through generate_image / publish_to_web first). No mask field — describe the region in prose. Latency 40s–350s. |
Localhost-only HTTP for native-app integration and scripting.
| Endpoint | Method | Description |
|---|---|---|
/health | GET | Liveness → {"status":"ok","version":"..."} |
/status | GET | Connection state, active agent, uptime, version |
/agents | GET | List named agents |
/sessions | GET | List sessions, optional ?agent= filter |
/sessions/{id} | GET | Full session with messages, ?agent=<name> |
/sessions/{id} | PATCH | Update title, pinned, favorite (any subset) |
/sessions/{id}/edit | POST | Truncate history at index, re-run with new content |
/sessions/{id}/reset | POST | Clear session history in place (named agent only) |
/sessions/search | GET | Search session history, ?q=<query>&agent=<name> |
/message | POST | Send a message; supports HITL injection |
/migrate/claude-code/preview | POST | Scan ~/.claude/ and return what would be imported (dry-run) |
/migrate/claude-code/apply | POST | Execute a previewed import — copies agents, skills, instructions from Claude Code |
/config/reload | POST | Reload config, restart watchers and heartbeat managers |
/events | GET | SSE stream of daemon events (agent_reply, heartbeat_alert, …) |
/shutdown | POST | Graceful shutdown (used by shan daemon stop) |
Send a message:
```bash
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。
总体来看,Kocoro 是一款质量良好的MCP工具,在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态,建议收藏备用,结合自身场景选择合适时机引入使用。
| 原始名称 | Kocoro |
| 原始描述 | 开源MCP工具:An AI cowork agent for your Mac — local computer access, Slack/LINE channels, MC。⭐270 · Go |
| Topics | mcpgo |
| GitHub | https://github.com/Kocoro-lab/Kocoro |
| License | MIT |
| 语言 | Go |
收录时间:2026-05-22 · 更新时间:2026-05-22 · 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