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GEODE
🔌
MCP工具

GEODE

基于 Python · 让 AI 助手直接操作你的系统与工具
英文名:geode
⭐ 6 Stars 🍴 2 Forks 💻 Python 📄 Apache-2.0 🏷 AI 8.0分
8.0AI 综合评分
mcppython自动化
✦ AI Skill Hub 推荐

GEODE 是 AI Skill Hub 本期精选MCP工具之一。综合评分 8.0 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。

📚 深度解析

GEODE 是一款基于 MCP(Model Context Protocol)标准协议的 AI 工具扩展。MCP 协议由 Anthropic 开发并开源,旨在建立 AI 模型与外部工具之间的标准化通信接口,目前已被 Claude Desktop、Claude Code、Cursor 等主流 AI 工具采纳。

通过安装 GEODE,你的 AI 助手将获得额外的工具调用能力,可以用自然语言直接操控该工具的功能,无需学习复杂的命令行语法。MCP 工具的核心价值在于"一次配置,永久增强"——配置完成后,每次与 AI 对话时都可以无缝调用这些工具。

在技术实现上,MCP 工具通过标准的 JSON-RPC 协议与 AI 客户端通信,工具的功能以"工具列表"的形式暴露给 AI 模型,AI 可以按需调用。GEODE 提供了结构化的工具调用接口,使 AI 模型能够精确地理解和使用每个功能点,显著降低 AI 在工具使用上的错误率。

与传统的 API 集成相比,MCP 工具的优势在于无需编写代码——用户只需在配置文件中添加几行 JSON,即可让 AI 获得全新能力。AI Skill Hub 将 GEODE 评为 AI 评分 8.0 分,属于同类工具中的优质选择。

📋 工具概览

GEODE 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。

GitHub Stars
⭐ 6
开发语言
Python
支持平台
Windows / macOS / Linux
维护状态
轻量级项目,按需更新
开源协议
Apache-2.0
AI 综合评分
8.0 分
工具类型
MCP工具
Forks
2

📖 中文文档

以下内容由 AI Skill Hub 根据项目信息自动整理,如需查看完整原始文档请访问底部「原始来源」。

GEODE 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。

📌 核心特色
  • 通过标准 MCP 协议与 Claude、Cursor 等主流 AI 客户端深度集成
  • 提供结构化工具调用接口,显著降低 AI 集成复杂度
  • 支持 Claude Desktop 和 Claude Code 无缝接入,开箱即用
  • 可与其他 MCP 工具组合叠加,构建完整 AI 工作站
  • 轻量无侵入设计,不影响现有系统架构
🎯 主要使用场景
  • 在 Claude Desktop 对话中直接调用本地工具,实现 AI 与系统的深度联动
  • 通过自然语言驱动复杂的多步骤自动化任务,代替繁琐手动操作
  • 将多个 MCP 工具组合使用,构建个人专属 AI 工作站
以下安装命令基于项目开发语言和类型自动生成,实际以官方 README 为准。
安装命令
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/mangowhoiscloud/geode

# 方式二:手动配置 claude_desktop_config.json
{
  "mcpServers": {
    "geode": {
      "command": "npx",
      "args": ["-y", "geode"]
    }
  }
}

# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
📋 安装步骤说明
  1. 确认已安装 Node.js(v18 或以上版本)
  2. 打开 Claude Desktop 或 Claude Code 的 MCP 配置文件
  3. 按「交给 Agent 安装 → Claude Desktop」标签中的 JSON 配置填入 mcpServers 字段
  4. 保存配置文件并重启 Claude 客户端
  5. 重启后,在对话中即可使用本工具
以下用法示例由 AI Skill Hub 整理,涵盖最常见的使用场景。
常用命令 / 代码示例
# 安装后在 Claude 对话中直接使用
# 示例:
用户: 请帮我用 GEODE 执行以下任务...
Claude: [自动调用 GEODE 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"
以下配置示例基于典型使用场景生成,具体参数请参照官方文档调整。
配置示例
// claude_desktop_config.json 配置示例
{
  "mcpServers": {
    "geode": {
      "command": "npx",
      "args": ["-y", "geode"],
      "env": {
        // "API_KEY": "your-api-key-here"
      }
    }
  }
}

// 保存后重启 Claude Desktop 生效
📑 README 深度解析 真实文档 完整度 75/100 含工作流图 查看 GitHub 原文 →
以下内容由系统直接从 GitHub README 解析整理,保留代码块、表格与列表结构。

简介

<p align="center"> <img src="assets/geode-mascot.png" alt="GEODE — Autonomous Execution Harness" width="360" /> </p>

<p align="center"> <img src="https://img.shields.io/badge/while(tool__use)-agentic%20loop-1e293b?style=flat-square" alt="while(tool_use)"> <img src="https://img.shields.io/badge/self--improving-non--parametric-1e293b?style=flat-square" alt="Self-improving (non-parametric)"> <img src="https://img.shields.io/badge/LangGraph-StateGraph-1e293b?style=flat-square" alt="LangGraph"> <a href="https://github.com/mangowhoiscloud/geode/actions"><img src="https://img.shields.io/github/actions/workflow/status/mangowhoiscloud/geode/ci.yml?style=flat-square&label=ci&logo=github&logoColor=white" alt="CI"></a> </p>

<p align="center"> <img src="https://img.shields.io/badge/Anthropic-Opus_4.7-cc785c?style=flat-square&logo=anthropic&logoColor=white" alt="Anthropic Opus 4.7"> <img src="https://img.shields.io/badge/OpenAI-GPT--5.5-412991?style=flat-square&logo=openai&logoColor=white" alt="OpenAI GPT-5.5"> <img src="https://img.shields.io/badge/ZhipuAI-GLM--5.1-1a73e8?style=flat-square" alt="ZhipuAI GLM-5.1"> </p>

<p align="center"> <a href="https://mangowhoiscloud.github.io/geode/">Site</a> · <a href="https://mangowhoiscloud.github.io/geode/docs">Docs</a> · <a href="https://mangowhoiscloud.github.io/geode/self-improving/">Self-improving hub</a> · <a href="README.ko.md">한국어</a> </p>

What's inside

FeatureWhat it does
**while(tool_use) loop**The single primitive every behavior is built on. Sub-agents, plans, batches are all instances of the same loop
**Self-improving outer loop**Mutates GEODE's own scaffolding, audits each change against an adversarial safety rubric, and promotes only on a real gain. See [the closed loop](https://mangowhoiscloud.github.io/geode/docs/capabilities/autoresearch)
**Agentic tools + MCP catalog**Web search, file ops, scheduling, memory, calendar, Slack/Discord, Korean job-board search, plus the Anthropic-published MCP registry (cached at ~/.geode/mcp/registry-cache.json). Auto-installed on first use
**3-provider failover**Anthropic + OpenAI + ZhipuAI. Subscription OAuth (Codex) auto-detected; pay-as-you-go API keys also work; failover is in-provider only (no surprise cross-vendor charges, v0.53.0 governance)
**5-tier memory**SOUL (0) → User Profile (0.5) → Organization (1) → Project (2) → Session (3). Persistent, survives daemon restarts
**Plan-mode + audit trail**create_plan + approve_plan + list_plans for multi-step work. Disk-persistent (.geode/plans.json), survives restarts
**Long-running daemon**geode serve runs as background daemon. Slack / Discord / Telegram pollers + scheduler tick + IPC for the thin CLI
**Sub-agents**Full inheritance of parent capability, depth/cost guards, isolation by Lane
**Core verification**Guardrails G1-G4 (structural) + Cross-LLM (inter-model, Krippendorff α ≥ 0.67) + Rights Risk (legal). External packages can add specialized bias / calibration layers

---

Prerequisites — what you need first

<details> <summary><strong>Don't know what these are?</strong> Click here for a 1-line explainer of each.</summary>

  • Python 3.12+ — the language GEODE is written in. Most laptops don't have a recent enough version. Install from python.org/downloads (download the macOS or Windows installer, click through).
  • Git — how you copy GEODE's source code from GitHub. Mac: comes with Xcode Command Line Tools (xcode-select --install). Windows: git-scm.com installer.
  • uv — a fast Python package manager (replaces pip). One-line install: copy the curl command below into Terminal/PowerShell.

If any of these fail, see Troubleshooting below. </details>

ToolInstallVerify
Python 3.12+[python.org/downloads](https://www.python.org/downloads/)python3 --version
Git[git-scm.com](https://git-scm.com/)git --version
uvcurl -LsSf https://astral.sh/uv/install.sh \| shuv --version

Setup in 5 minutes

Step 1 — Install GEODE

GEODE's PyPI distribution is geode-agent. It installs the geode command.

uv tool install geode-agent
geode version

If the current release has not been published to PyPI yet, or you are developing GEODE itself, install from source instead:

git clone https://github.com/mangowhoiscloud/geode.git
cd geode
uv sync                              # installs dependencies (~30s)
uv tool install -e . --force         # makes `geode` available everywhere

Step 2 — Run the setup wizard

geode setup

The wizard offers three paths: ChatGPT subscription (auto-detects codex auth login if you've already done it), API key (paste and go), or skip into dry-run mode for now. Pick whichever fits.

If you already ran codex auth login before installing GEODE, you can skip this step entirely — the next geode invocation will detect the token and start.

Uninstalling

geode uninstall removes GEODE runtime data, stops the daemon, and removes the geode-agent uv tool install. Preview first if you want to see exactly what would be removed:

geode uninstall --dry-run
geode uninstall

If you only want to remove the PyPI-installed CLI and keep runtime data under ~/.geode/, use uv directly:

uv tool uninstall geode-agent

Useful partial removal modes:

geode uninstall --keep-config   # keep .env and config.toml
geode uninstall --keep-data     # keep vault, identity, and user profile data
geode uninstall --force         # skip confirmations for automation

Verify removal:

which geode               # should print nothing
uv tool list | grep geode # should not list geode-agent
pgrep -f "geode serve"    # should print nothing

---

Optional — Hook into Slack / Discord / Telegram

Once GEODE works in your terminal, you can let it answer on the messaging channels you already use:

geode serve                          # starts the always-on Gateway daemon

Configure channel bindings in .geode/config.toml (Slack bot token, Discord webhook, etc.). See docs/setup.md → Gateway for the full setup. After that, mentioning the bot in a channel routes the message into the same agent loop you use locally.

Optional — Self-improving loop config (`~/.geode/config.toml`)

Tune the autoresearch / seed-generation / petri audit drivers — model picks, dim set, banner thresholds, PAYG fallback policy — by copying the [self_improving_loop.*] sections from docs/examples/self_improving_loop.config.toml.example into ~/.geode/config.toml. Absent sections fall back to documented defaults. To migrate per-role entries from the legacy ~/.geode/petri.toml:

geode config migrate-petri-toml          # dry-run preview
geode config migrate-petri-toml --yes    # append [self_improving_loop.petri.*] to config.toml

---

Step 3 — Pick a path (manual reference)

The wizard above covers everything below; this section exists as a manual reference for what each path actually does.

---

Path A — ChatGPT subscription (the recommended path for OpenAI users)

Codex CLI signs you in once. GEODE picks up the token from ~/.codex/auth.json and uses it for every call. Your subscription pays the bill; nothing extra to set up.

brew install codex                    # macOS  (or: npm install -g @openai/codex)
codex auth login                      # opens a browser; sign in with your ChatGPT account
geode                                 # done. GEODE finds the token automatically.

Plans that work (per the official Codex CLI docs): Plus, Pro, Business, Edu, Enterprise.

Quotas (OpenAI-published, per 5-hour window): roughly 15–80 messages on Plus, up to 1,600 on Pro 20x. Edu and Enterprise have no fixed cap; usage scales with your workspace credits. Your admin needs to flip "Allow members to use Codex Local" before sign-in works on those tiers.

Tier notes: - gpt-5.5 is subscription-only. API-key users (Path B) top out at gpt-5.4. If you want 5.5, you need ChatGPT. - ChatGPT Team is not currently supported by Codex CLI. Team users should use Path B. - Free / Go appear on OpenAI's pricing page but aren't listed in the CLI README. Treat them as best-effort; if it works, great, but no promises.

When the token nears expiry, GEODE refreshes it on its own (120 seconds before, plus a 401 retry). You shouldn't see this happen.

Why Claude Pro isn't a Path A option. Anthropic's terms changed on 2026-01-09: third-party tools may no longer reuse the Claude Code OAuth token. GEODE doesn't read ~/.claude/.credentials.json to keep your account safe. The only Anthropic path GEODE accepts is an API key (Path B). (Reference)

---

Path B — API key (pay-as-you-go)

For Anthropic users (any tier, including Claude Pro / Max — OAuth isn't available), ChatGPT Team users, and anyone without a paid OpenAI subscription. You buy API credits directly. New Anthropic accounts get $5 in free credits, enough for hundreds of prompts.

Get an Anthropic API key (4 clicks):

  1. Sign up at console.anthropic.com
  2. Top-right menu → SettingsAPI Keys
  3. Click Create Key → name it "geode" → Copy the sk-ant-... string
  4. Save it where GEODE will find it:
mkdir -p ~/.geode
echo 'ANTHROPIC_API_KEY=sk-ant-paste-your-key-here' > ~/.geode/.env
chmod 600 ~/.geode/.env

Want OpenAI or ZhipuAI GLM instead? Add OPENAI_API_KEY=sk-proj-... or ZAI_API_KEY=... to the same file. GEODE picks whichever is available.

What it costs in practice. A single prompt runs around 3,000 tokens, about $0.01. A research session with ten tool calls usually lands between $0.05 and $0.30. Your $5 free credit lasts roughly 500 prompts. Set cost_limit_usd=5 in .env if you want a hard cap.

---

How GEODE compares

A qualitative read on where GEODE sits next to the frontier harnesses (Claude Code, Codex CLI, OpenClaw) as of May 2026. This is about posture, not benchmarks. Marker legend: ✅✅ leader on the axis · ✅ supported · ⚠️ partial / qualified · ❌ absent · n/a not applicable.

<details> <summary><strong>A. Runtime posture</strong> — how the agent stays alive</summary>

Claude CodeCodex CLIOpenClaw**GEODE**
Always-on daemon❌ per-invocation⚠️ opt-in codex remote-control✅✅ launchd / systemd control planegeode serve daemon
Native scheduler (cron)❌ (claude.ai web-only)❌ (Codex Cloud Automations only — [issue #8317](https://github.com/openai/codex/issues/8317))cron add/edit/list CLI✅ cron + event triggers
Thin CLI ↔ daemon IPC⚠️ remote-control server mode✅ Gateway / Agent split✅ IPC server
Sub-agent isolation✅ Agent tool + run_in_backgroundmulti_agent feature✅✅ Lane Queue + Session bindings✅ Lane + depth / cost guard
Session resume / fork✅ JSONL transcripts/resume + /fork slash commands✅ Session bindings with TTL✅ session resume

</details>

<details> <summary><strong>B. Channels & UX surfaces</strong> — how it reaches users</summary>

Claude CodeCodex CLIOpenClaw**GEODE**
Slack❌ (MCP plugin possible)⚠️ Codex Cloud only, not CLI✅ Socket Mode, first-class✅ Socket Mode, first-class
Discord / Telegram / other chat✅✅ many channels (Discord, Telegram, WhatsApp, Signal, iMessage, Teams, Matrix, Feishu, LINE, ...)✅ Discord + Telegram pollers
IDE plugin❌ (Chrome MCP extension only)✅✅ VS Code · JetBrains · Cursor · Windsurf
Web UI✅ claude.ai/code✅ Codex Cloud⚠️ WebChat plugin❌ (docs site only)
MCP server catalog✅ first-class✅ first-class✅ first-class✅ Anthropic-published registry (cached at ~/.geode/mcp/registry-cache.json)

</details>

<details> <summary><strong>C. LLM provider & cost governance</strong></summary>

Claude CodeCodex CLIOpenClaw**GEODE**
Multi-provider failover✅ Anthropic + AWS Bedrock + Google Vertex (env routing)✅✅ OpenAI + Azure + Bedrock + Ollama + any OpenAI-compatible (model_providers config)auth.order cooldown-based auto-failover✅ Anthropic + OpenAI + ZhipuAI, in-provider only
Subscription OAuth tier✅ Pro / Max✅✅ Plus · Pro · Business · Edu · Enterprise⚠️ OpenAI + Gemini onboarding⚠️ ChatGPT only (Plus / Pro / Business / Edu / Enterprise) — Anthropic ToS (2026-01-09) blocks third-party Claude OAuth
Token / cost budget guard⚠️ cache token tracking only⚠️ retry caps (request_max_retries)⚠️ partial✅ explicit token + cost budget governance
Context overflow handling✅ autocompaction⚠️ skills progressive disclosure + fork✅ compaction + transcript streaming✅✅ layered context-overflow handling
Cross-vendor failover policy⚠️ manual model_providers switch✅ automatic❌ by design (no surprise cross-vendor charges)

</details>

<details> <summary><strong>D. Persistence, memory & verification</strong></summary>

Claude CodeCodex CLIOpenClaw**GEODE**
Memory tiers⚠️ user / project / local settings merge✅ hierarchical AGENTS.md (global ~/.codex/ + repo + nested dirs)⚠️ session-scoped✅✅ **multi-tier** (SOUL · User · Org · Project · Session)
Disk-persistent plans✅ TodoWrite persistence⚠️ via resumable threads✅ task registry.geode/plans.json
Permission / sandbox layers✅ default / auto / bypass modes + Confirmation UIsandbox_mode (read-only / workspace-write / danger-full-access)✅✅ Policy Chain across many audit surfaces✅ Policy Chain + tool gates
Multi-layer guardrails⚠️ permission + hooks⚠️ hooks + sandboxaudit.runtime engine✅✅ **core verification** (G1-G4 + Cross-LLM Krippendorff α ≥ 0.67 + Rights Risk, plugin extension points for bias/calibration)
Hook events⚠️ PreToolUse / PostToolUse / SessionStart / Notification / ConfigChange⚠️ SessionStart / UserPromptSubmit / PreToolUse / PostToolUse / PermissionRequest / Stop✅ several event types · many bundled handlers✅✅ broad event surface (docs/architecture/hook-system.md)

</details>

<details> <summary><strong>E. Extensibility & observability</strong></summary>

Claude CodeCodex CLIOpenClaw**GEODE**
Plugin / extension surfaces✅ manifest + marketplace (user / project / local scopes)/plugins slash command + plugin sharing✅✅ extension points (Channel · Tool · Skill · Hook) via @openclaw/plugin-sdk✅ runtime SkillRegistry + MCP/tool surfaces
Skill system✅ Deferred tools + SKILL.md manifest✅ SKILL.md + progressive disclosure (.agents/skills/)✅ skill filter + archive upload✅ runtime SkillRegistry across bundled/global/project scopes
**Swappable pipeline DAG**⚠️ flows (channel-setup / doctor / provider — not a DAG abstraction)⚠️ external package responsibility; GEODE core no longer ships a pipeline port
Trace / replay / Run Logtengu_* telemetry + /insights HTML⚠️ /status + /debug-config only✅ ACP session lineage + Task Registry✅ Native RunLog + Petri eval integration
Self-improving safety loop✅✅ outer loop: scaffold mutation + adversarial safety audit + (1+1) promote/revert
Cross-LLM verification✅✅ Krippendorff α ≥ 0.67 inter-rater agreement gate

</details>

---

Use Claude Code or Codex for short coding sessions inside an IDE or via cloud sync. Use OpenClaw to run a multi-channel chat agent fleet across many messaging surfaces. Use GEODE when an agent must work over hours or days with multi-tier memory, multi-layer verification, scheduling, and daemon-backed tool execution, and when you want that agent to keep improving its own scaffolding under a safety floor.

Sources — Claude Code (reverse-engineered reference). Codex CLI release notes + developers.openai.com/codex/config-reference + github.com/openai/codex. OpenClaw (TypeScript). GEODE — CHANGELOG.md and the self-improving hub.

---

<details> <summary><strong>Architecture overview</strong> (for contributors)</summary>

GEODE has two control layers:

  • Scaffold (production) — Claude Code + CLAUDE.md + development Skills + CI Hooks. The external harness that produces GEODE's code and guarantees quality. The self-improving outer loop also mutates parts of this scaffold.
  • GEODE Runtime (agent)while(tool_use) loop + agentic tools + native ToolRegistry + runtime Skills + runtime Hooks + multi-layer Verification. The internal system of the autonomously executing agent.

4-Layer Stack (Model → Runtime → Harness → Agent) + Sub-Agent System + 5-Tier Memory.

graph LR AG["Agent
AgenticLoop, SubAgent
CLIPoller, Gateway"] --> HA["Harness
SessionLane, PolicyChain
TaskGraph, HookSystem"] HA --> RT["Runtime
Agentic tools, MCP catalog
Memory, Skills"] RT --> MD["Model
Claude, OpenAI, GLM"] style AG fill:#1e293b,stroke:#3b82f6,color:#e2e8f0 style HA fill:#1e293b,stroke:#f59e0b,color:#e2e8f0 style RT fill:#1e293b,stroke:#10b981,color:#e2e8f0 style MD fill:#1e293b,stroke:#8b5cf6,color:#e2e8f0
LayerCoreEntry points
**Agent**AgenticLoop, SubAgentManager, CLIPoller, Gatewaycore/cli/, core/gateway/
**Harness**SessionLane, LaneQueue, PolicyChain, TaskGraph, HookSystemcore/orchestration/, core/hooks/
**Runtime**Agentic tools, native ToolRegistry, MCP Catalog (Anthropic registry plus project-configured servers), runtime Skills, Memory (multi-tier), PlanStorecore/tools/, core/memory/, core/orchestration/plan_store.py
**Model**ClaudeAdapter, OpenAIAdapter, CodexAdapter, GLMAdaptercore/llm/

.geode/ — agent context lifecycle (5-tier hierarchy assembled into every LLM call):

Tier 0    SOUL            GEODE.md — agent identity + constraints
Tier 0.5  User Profile    ~/.geode/user_profile/ — role, expertise, language
Tier 1    Organization    Cross-project data (signals, history)
Tier 2    Project         .geode/memory/PROJECT.md — analysis history (LRU-50)
Tier 3    Session         In-memory — conversation, tool results, plans
.geode/
├── config.toml         # Gateway, MCP servers, model
├── memory/             # T2: Project Memory (LRU rotate)
├── rules/              # Auto-generated project rules
├── vault/              # Permanent artifacts (reports, research)
├── skills/             # project runtime skills (5-tier discovery)
├── plans.json          # Disk-persistent PlanStore (v0.53.3)
└── result_cache/       # Pipeline LRU (SHA-256, 24h TTL)

Full architecture → | Hook System → | Wiring Audit →

</details>

<details> <summary><strong>Development workflow (Scaffold)</strong></summary>

CANNOT (guardrails) before CAN (freedom). A 7-step workflow plus quality gates. The CI ratchet (pytest, mypy, ruff, import-order, test-count) must pass before any merge. Test count is monotonically increasing only.

GateCommandTarget
Lintuv run ruff check core/ tests/0 errors
Typeuv run mypy core/0 errors
Testuv run pytest tests/ -qall pass

See CONTRIBUTING.md and docs/workflow.md.

</details>

<details> <summary><strong>Why — motivation</strong></summary>

In 2026, AI coding agents have made remarkable progress. They read, write, fix, and test code autonomously. But how much of real work is actually coding? Research, document analysis, scheduling, notifications, data pipelines, multi-axis evaluation for decision-making — the space requiring autonomous execution beyond coding is far broader.

Yet the core of all autonomous behavior is surprisingly simple: an LLM calls tools, observes results, decides the next action — a while(tool_use) loop. Claude Code, Codex, OpenClaw — all frontier harnesses stand on this primitive. GEODE generalizes it into a daemon-backed, memoryful runtime for long-running tool work.

</details>

---

Troubleshooting

Run geode doctor first. It checks Python version, geode PATH, ~/.geode/.env, Codex CLI OAuth, ProfileStore, the serve socket, and ~/.local/bin PATH — and prints a concrete fix command for each failure. The expanders below cover the same ground in narrative form.

<details> <summary><strong>"command not found: python3"</strong> — Python isn't installed or isn't on your PATH.</summary>

Mac: xcode-select --install then brew install python@3.12. Windows: download the installer from python.org and check "Add Python to PATH" during setup. Verify with python3 --version — must be 3.12 or higher. </details>

<details> <summary><strong>"command not found: uv"</strong> — uv isn't on your PATH yet.</summary>

The install script writes uv to ~/.local/bin. Either restart your terminal, or run source ~/.bashrc (bash) / source ~/.zshrc (zsh). Verify with uv --version. </details>

<details> <summary><strong>"command not found: geode"</strong> — the global install hasn't run.</summary>

For a PyPI install, run uv tool install geode-agent. For a source checkout, run uv tool install -e . --force from the geode/ directory. Both paths put the geode command in ~/.local/bin/. If that directory isn't on your PATH, add export PATH="$HOME/.local/bin:$PATH" to your shell config. </details>

<details> <summary><strong>"401 Unauthorized" or "Invalid API key"</strong> — wrong key, expired key, or wrong file location.</summary>

Check cat ~/.geode/.env and confirm the key starts with sk-ant- (Anthropic), sk-proj- (OpenAI), or id.secret (ZhipuAI GLM). Make sure there are no extra spaces or quote characters. If you used the ChatGPT subscription path (Path A), re-run codex auth login to refresh the OAuth token. </details>

<details> <summary><strong>"Address already in use" when running geode serve</strong> — daemon is already running.</summary>

ps aux | grep "geode serve" to find the PID, then kill <PID>. Or use geode serve --port <other> to pick a different port. </details>

<details> <summary><strong>The model doesn't seem to use my tools / runs in circles.</strong></summary>

Check geode model — some models are better at tool use than others. Default is claude-opus-4-7 (best). If you're on gpt-5.5, set effort: "high" in .geode/config.toml. Run tail -f ~/.geode/logs/serve.log to see what the model is actually doing. </details>

<details> <summary><strong>I want to see what GEODE is doing under the hood.</strong></summary>

tail -f ~/.geode/logs/serve.log (or whichever log file you redirected when starting geode serve manually). Every LLM call, tool invocation, and decision is logged with timing. The core.audit.diagnostics fa4 channel writes per-month files under ~/.geode/diagnostics/<YYYY-MM>.log for cross-process traces. </details>

<details> <summary><strong>How do I update?</strong></summary>

uv tool upgrade geode-agent   # PyPI install
geode update                  # source checkout
</details>

---

📚 实用指南(长尾问题)
适合谁
  • 需要让 Claude / Cursor 操作本地工具的 AI 工程师
最佳实践
  • 配置 MCP 服务器时建议使用 stdio 传输 + JSON-RPC,避免暴露公网
常见错误
  • API key 直接提交到 git 仓库(请用 .env 并加入 .gitignore)
  • MCP 配置路径拼错或权限不足,重启 Claude Desktop 才生效
  • Python 依赖冲突:建议用 venv / uv 隔离环境
部署方案
  • 云端托管:可放在 Vercel / Railway / Fly.io 等 PaaS 平台
相关搜索
geode 中文教程geode 安装报错怎么办geode MCP 配置geode 与同类工具对比geode 最佳实践geode 适合谁用

⚡ 核心功能

👥 适合谁
  • 需要让 Claude / Cursor 操作本地工具的 AI 工程师
⭐ 最佳实践
  • 配置 MCP 服务器时建议使用 stdio 传输 + JSON-RPC,避免暴露公网
⚠️ 常见错误
  • API key 直接提交到 git 仓库(请用 .env 并加入 .gitignore)
  • MCP 配置路径拼错或权限不足,重启 Claude Desktop 才生效
  • Python 依赖冲突:建议用 venv / uv 隔离环境

👥 适合人群

Claude Desktop / Claude Code 用户AI 工具开发者需要扩展 AI 能力的专业人士自动化工程师

🎯 使用场景

  • 在 Claude Desktop 对话中直接调用本地工具,实现 AI 与系统的深度联动
  • 通过自然语言驱动复杂的多步骤自动化任务,代替繁琐手动操作
  • 将多个 MCP 工具组合使用,构建个人专属 AI 工作站

⚖️ 优点与不足

✅ 优点
  • +Apache-2.0 协议,可免费商用
  • +标准化 MCP 协议,生态互联性强
  • +与 Claude 官方生态无缝对接
  • +即插即用,配置简单快捷
⚠️ 不足
  • 依赖 Claude 客户端,非 Claude 用户无法使用
  • MCP 协议仍在持续演进,接口可能变更
  • 需要一定的配置步骤
⚠️ 使用须知

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。

📄 License 说明

✅ Apache 2.0 — 宽松开源协议,可商用,需保留版权声明和 NOTICE 文件,含专利授权条款。

🔗 相关工具推荐

📚 相关教程推荐
📰 相关 AI 新闻
🍿 AI 圈相关吃瓜
🗺️ 相关解决方案
🧩 你可能还需要
基于当前 Skill 的能力图谱,自动补全的工具组合

❓ 常见问题 FAQ

geode 是一款Python开发的AI辅助工具。开源MCP工具:GEODE v0.99.70: 범용 자율 실행 에이전트 하네스 · while(tool_use) AgenticLoop · 54 Tools + 13 。⭐6 · Python 主要应用场景包括:自动化执行和集成。
💡 AI Skill Hub 点评

经综合评估,GEODE 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。

⬇️ 获取与下载
⬇ 下载源码 ZIP

✅ Apache-2.0 协议 · 可免费商用 · 直接从 aiskill88 服务器下载,无需跳转 GitHub

📚 深入学习 GEODE
查看分步骤安装教程和完整使用指南,快速上手这款工具
🌐 原始信息
原始名称 geode
原始描述 开源MCP工具:GEODE v0.99.70: 범용 자율 실행 에이전트 하네스 · while(tool_use) AgenticLoop · 54 Tools + 13 。⭐6 · Python
Topics mcppython自动化
GitHub https://github.com/mangowhoiscloud/geode
License Apache-2.0
语言 Python
🔗 原始来源
🐙 GitHub 仓库  https://github.com/mangowhoiscloud/geode

收录时间:2026-05-29 · 更新时间:2026-05-30 · License:Apache-2.0 · AI Skill Hub 不对第三方内容的准确性作法律背书。