AI Skill Hub 推荐使用:Zaxy 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。
Zaxy 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。
Zaxy 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/syndicalt/zaxy
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"zaxy": {
"command": "npx",
"args": ["-y", "zaxy"]
}
}
}
# 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 Zaxy 执行以下任务... Claude: [自动调用 Zaxy 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": {
"zaxy": {
"command": "npx",
"args": ["-y", "zaxy"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
Production memory for agent teams that need receipts.
Zaxy turns agent context into an auditable project memory fabric. It captures parent missions, worker sessions, tool observations, cited findings, conflict review, approval packets, and accepted merge-back into one durable history that can be queried, replayed, and inspected.
Under the hood, Zaxy uses Eventloom append-only JSONL as the source of truth and an embedded LadybugDB graph projection for local reasoning. It is built for agents that need to remember what happened, cite where it came from, and avoid turning project state into a pile of markdown files and vector chunks.
The embedded LadybugDB graph projection is the default local runtime.
The plain install uses embedded LadybugDB. Install zaxy-memory[neo4j] only for the optional Neo4j sidecar, and zaxy-memory[pathlight] only for Pathlight tracing.
valid_from, valid_to).zaxy-memory[pathlight]../scripts/generate-certs.sh .certs docker compose --profile integration up -d neo4j-test neo4j-tls pytest -m integration --no-cov
pipx install zaxy-memory
zaxy init
zaxy memory log --eventloom-path .eventloom --limit 5
zaxy memory bootstrap --eventloom-path .eventloom
zaxy doctor --eventloom-path .eventloom
The PyPI distribution is zaxy-memory; the import package and console command are still zaxy. Bare zaxy init sets up the local embedded graph posture, repo-local profile, deterministic capture config, genesis event, heartbeat, and MCP guidance. For Codex, the printed activation launcher starts the managed capture watcher when the local capture config is present; pass --capture start only when you want init itself to start the watcher before opening Codex. The default human output is compact and action-first; add --verbose when you need the full setup diagnostics, optional checks, fallback commands, resume guidance, and notes. For automation, zaxy init --json keeps the raw onboarding fields and adds setup.status, setup.issues, setup.pending, readiness.status, readiness.reasons, readiness.actions, and structured readiness.action_items for both commands and non-command review tasks. Each structured action carries label, command, original source, and hints for compact-output tips such as activation <task> replacement and path-stable command guidance. Installers can render those tips without parsing prose. It also includes setup.summary, readiness.summary, readiness.required_action_count, and readiness.reason_count, so client UIs can render compact status without parsing human output. It also separates readiness.blocking_diagnostics from readiness.non_blocking_diagnostics so scripts can distinguish setup completion, required actions, and advisory doctor warnings before relying on live memory.
For Codex, zaxy init --codex-mcp-install auto is the default. It writes or reuses the user-level Codex MCP config when that can be done without replacing an existing zaxy server entry. If no safe config target exists, it prints the copyable codex mcp add command. If an existing zaxy entry differs, it asks you to review that config before replacing it because Codex can silently replace servers with the same name. Use an explicit mode when you need to force one side of that decision after review:
```bash zaxy init --codex-mcp-install user
Both Codex paths keep the server workspace-neutral. After init, start or
restart Codex through the printed `zaxy activate codex ... --launch` command so
the MCP server list and Zaxy activation packet are loaded together. The printed
command includes explicit `--eventloom-path` and `--workspace-root` values, so
it still targets the initialized repo when copied from another shell.
Run the single-agent memory example:
bash python examples/single_agent_memory.py
Your local data lives under `.eventloom/` as one append-only JSONL file per
session.
For Claude Code instead of Codex:
bash zaxy init . --domain my-project --preset local-claude --infra check
For Hermes Agent:
bash zaxy ide-config hermes --install ```
For repository development, use pip install -e ".[dev]", ./scripts/setup.sh, and zaxy status. Start Docker sidecars only for integration tests or explicit backend comparisons. Production setup writes Docker secret files under ./secrets/; see docs/deployment.md.
scripts/validate-deployment.sh --root .
scripts/build-dist.sh --root .
Zaxy是一个有潜力的开源MCP工具,值得关注
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,Zaxy 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 | zaxy |
| Topics | mcpaiai-agentsai-memoryllm-toolspython |
| GitHub | https://github.com/syndicalt/zaxy |
| License | MIT |
| 语言 | Python |
收录时间:2026-06-13 · 更新时间:2026-06-13 · 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