
Claude Octopus
io.github.xiaolai由 GitHub 帳號 xiaolai 發布v1.1.10更新於 Oct 24, 2026
Spawn multiple specialized Claude Code agents as MCP servers, each independently configured.
發布方自己的服務:Octopus.do
概覽
封裝 Claude Agent SDK,讓助理以 MCP 工具形式執行多個獨立設定的 Claude Code 代理,並提供時間軸、工作階段紀錄與報告。
- 可以做什麼
- 向已設定的 Claude Code 代理送出任務,並依工作階段 ID 繼續對話,可逐次覆寫模型、工作目錄、工具限制、思考強度與預算。以不同模型、提示詞與工具集執行多個執行個體,每個執行個體各自成為獨立工具。把相關呼叫歸入同一次執行,並查詢跨代理時間軸。讀取完整工作階段紀錄,列出目前專案或所有專案的 Claude Code 工作階段歷史。為執行產生自包含的 HTML 報告,也可只暴露一個用來產生新代理設定的工廠精靈。
- 適用情境
- 適合在同一個 MCP 用戶端中使用多個專用 Claude Code 代理(例如唯讀審查者、測試撰寫者與便宜的快速助手),或需要追蹤並彙報多代理工作流程時使用。
- 執行需求
- 以 npm 套件形式透過 stdio 在本機執行,需要 Node.js 18 或更新版本,以及可用的 Claude Code CLI 安裝。驗證使用 ANTHROPIC_API_KEY 中的 Anthropic API 金鑰或 Claude Code OAuth 工作階段,未設定時從父行程繼承。設定透過 CLAUDE_* 環境變數完成。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Claude Octopus,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
README
Claude Octopus
One brain, many arms.
An MCP server that wraps the Claude Agent SDK, letting you run multiple specialized Claude Code agents — each with its own model, tools, system prompt, and personality — from any MCP client.
Why
Claude Code is powerful. But one instance does everything the same way. Sometimes you want a strict code reviewer that only reads files. A test writer that defaults to TDD. A cheap quick helper on Haiku. A deep thinker on Opus.
Claude Octopus lets you spin up as many of these as you need. Same binary, different configurations. Each one shows up as a separate tool in your MCP client.
Prerequisites
- Node.js >= 18
- Claude Code — the Claude Agent SDK is bundled as a dependency, but it spawns Claude Code under the hood, so you need a working
claudeCLI installation - Anthropic API key (
ANTHROPIC_API_KEYenv var) or an active Claude Code OAuth session
Install
Three paths, pick whichever matches your MCP client.
npm (most direct)
npx (no install needed)
Skip the install entirely — reference claude-octopus@latest in your .mcp.json and the client will fetch on demand (see Quick Start below).
MCP Registry
The server is published to the MCP Registry under the name io.github.xiaolai/claude-octopus. Registry-aware MCP clients can resolve and install it by that name without touching npm directly.
Quick Start
The fastest way to get started:
This interactive wizard lets you pick a template, detects your MCP client, and writes the config for you.
Or add to your .mcp.json manually:
This gives you six tools:
That's it — you have Claude Code as a tool, with full workflow observability built in.
Multiple Agents
The real power is running several instances with different configurations:
Your MCP client now sees distinct tools for each agent — code_reviewer, test_writer, quick_qa — each purpose-built.
Multi-Agent Orchestration
Agents can coordinate through a coordinator pattern: one agent has the others as inner MCP tools via CLAUDE_MCP_SERVERS, and its system prompt drives the pipeline.
The coordinator agent autonomously calls researcher, architect, etc. as MCP tools — fully autonomous, no human in the loop until it finishes. Every invocation is tracked in the shared timeline.
Agent Factory
Don't want to write configs by hand? Add a factory instance:
This exposes a single create_claude_code_mcp tool — an interactive wizard. Tell it what you want ("a strict code reviewer that only reads files") and it generates the .mcp.json entry for you, listing all available options you can customize.
In factory-only mode, no query tools are registered — just the wizard. This keeps routing clean: the factory creates agents, the agents do work.
Init Wizard
Don't want to edit JSON by hand? The init wizard gets you from zero to working in 30 seconds:
It auto-detects installed MCP clients (Claude Desktop, Claude Code, Cursor, Windsurf), merges with existing config, and warns before overwriting.
Skip the menu
Templates
Five built-in templates, battle-tested and ready to use:
Each agent comes pre-tuned with appropriate model, tools, effort level, and system prompt.
Dashboard
Monitor your agents in real time:
Opens a local web dashboard at http://localhost:3456 with:
- Live stats — total runs, invocations, cost, SDK turns, responses, errors
- Recent activity — agent cards for the latest run
- Run table — all runs with cost, duration, and status
- Auto-refresh — SSE connection pushes updates as agents run
The dashboard reads the same timeline index used by the _timeline and _report tools. No additional configuration needed.
Tools
Each non-factory instance exposes:
Query and reply parameters
Timeline
Every agent invocation is recorded in a lightweight JSONL index at ~/.claude-octopus/timelines/timeline.jsonl. This solves the multi-agent correlation problem: when several agents participate in a workflow, the timeline tracks which sessions belong to the same run, in what order they executed, and what role each played.
Full session transcripts stay in Claude Code's own storage (~/.claude/projects/). The timeline is just the table of contents — ~200 bytes per entry — that cross-references via session_id.
How it works
- Every
<name>and<name>_replycall appends one line to the timeline - If you pass
run_id, all agents sharing the samerun_idare grouped into one run - If you omit
run_id, one is auto-generated and returned in the response — pass it to subsequent agents to keep them grouped
Querying the timeline
Multi-agent workflow example
HTML Reports
Generate self-contained HTML reports with agent sequence visualization, cost breakdown, and collapsible transcripts. Dark theme, no external dependencies — one file, open in any browser.
Via MCP tool
Via CLI
What's in the report
- Run summary — agent count, total cost, duration, SDK turns, responses, tool calls
- Timeline bar — numbered dots for each agent (green = success, red = error)
- Agent cards — timing, cost, effort counters, session ID, prompt excerpt
- Collapsible transcripts — full tool calls, reasoning, and results per agent
Reading the effort counters
Three numbers describe how much work an invocation took. They are not interchangeable, and the first one is the one that surprises people:
When an agent calls several tools in parallel, num_turns climbs faster than
the number of visible responses. A run with 3 assistant responses issuing 4
tool calls reports num_turns: 5, response_groups: 3, tool_calls: 4.
maxTurns, meanwhile, is enforced against round trips: that same run
completes under maxTurns: 3 and aborts under maxTurns: 2. So size
maxTurns against responses, not against SDK turns.
Both new counters cover the main agent loop only — work inside a sub-agent
(Task) belongs to its own loop and is excluded. Timeline entries written by
older versions have neither, and render as — rather than as a false zero.
Configuration
All configuration is via environment variables in .mcp.json. Every env var is optional.
Identity
Agent
Prompts
Advanced
Timeline
Authentication
Leave both unset to inherit auth from the parent process. Set one per agent to use a different account or billing source.
Lists accept JSON arrays when values contain commas: ["path,with,comma", "/normal"]
Security
- Permission mode defaults to
default— tool executions prompt for approval unless you explicitly setbypassPermissions. cwdoverrides preserve agent knowledge — when the host overridescwd, the agent's configured base directory is automatically added toadditionalDirectoriesso it retains access to its own context.- Tool restrictions narrow, never widen — per-invocation
toolsintersects with the server restriction (can only remove tools, not add).disallowedToolsunions (can only block more). _replyand_transcripttools respect persistence — not registered whenCLAUDE_PERSIST_SESSION=false.- Timeline writes are best-effort — a failed timeline append never blocks or fails the primary query.
Architecture
How It Compares
Development
License
ISC - Xiaolai Li
來源:README.md,提交 af84244
工具
0版本歷史
1- v1.1.10最新Sep 16, 2026
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