GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
作者提供的说明(英文原文)
Fast single-binary server for Plane project management. Unofficial Rust port, 30 tools.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
PLANE_API_KEY, PLANE_WORKSPACE_SLUG, PLANE_BASE_URL标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
链接指向作者自己的文件;我们不托管也不重新打包它。打开文件后,Claude Desktop 会进行安装。
在终端中运行这条命令
运行前请先填写空着的值。
浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
PLANE_BASE_URL env这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月9日
注册名称已通过 GitHub 账户 ninerf 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
你需要填写:PLANE_API_KEY, PLANE_WORKSPACE_SLUG
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.1.1)于5天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 MCPB。
同一分类中有:GitHub, Desktop Commander, Cloudflare MCP
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
MCP server for terminal commands, file operations, and process management
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
A fast, single-binary Model Context Protocol (MCP) server for Plane project management. It lets AI agents such as Claude, Cursor and Codex work with Plane work items, comments, cycles, modules, pages and more.
It is a Rust port of the MIT-licensed Python plane-mcp-server: the same 30 tools and tool schemas, about 16x less memory, no Python runtime.
Unofficial. A community project, not affiliated with or endorsed by Plane.
MCP Registry name: mcp-name: io.github.ninerf/plane-mcp-rs
Download a binary from Releases and put it on your PATH. Clients that support MCP bundles can install plane-mcp-rs.mcpb from the same page. Or build it with Rust:
cargo install --git https://github.com/ninerf/plane-mcp-rs
| Variable | Required | Meaning |
|---|---|---|
PLANE_API_KEY | yes | Plane API key (Profile → Personal Access Tokens) |
PLANE_WORKSPACE_SLUG | yes | Workspace slug from your Plane URL |
PLANE_BASE_URL | no | Self-hosted URL; defaults to https://api.plane.so |
claude mcp add plane -e PLANE_API_KEY=your-key -e PLANE_WORKSPACE_SLUG=your-slug -- plane-mcp-rs --stdio
{
"mcpServers": { "plane": { "command": "plane-mcp-rs", "args": ["--stdio"], "env": { "PLANE_API_KEY": "your-key", "PLANE_WORKSPACE_SLUG": "your-slug" } } } }
One process can serve every agent on a machine. It binds to 127.0.0.1 only and has no authentication of its own, so don't expose the port.
plane-mcp-rs --port 8096
The endpoint is http://127.0.0.1:8096/servers/plane/mcp.
workitem, workitem_comment, workitem_activity, workitem_link, workitem_relation, workitem_attachment, workitem_type, workitem_property, work_log, project, project_estimate, state, label, member, workspace, module, cycle, milestone, intake, page, collection, template, initiative, customer, customer_property, customer_request, release, release_label, release_tag, get_pql_reference.
The upstream server's retired tool names (169 aliases such as create_work_item) still work.
workitem list leaves out descriptions unless you pass fields, which roughly halves its output. Use retrieve for the full item.structuredContent copy.[].upload_from_url checks every resolved address and every redirect against private networks.Measured on one Windows 11 workstation against one self-hosted Plane instance, with plane-mcp-server 0.3.3 already tuned for a fair comparison (one server process, no mcp-proxy, payload logging off, the same lean workitem list). A stock install uses more. Your numbers will differ.
| Rust | Python | ||
|---|---|---|---|
| Memory, idle (working set) | 7.6 MB | 127.9 MB | 17x less |
| Memory, after load | 12.8 MB | 135.8 MB | 11x less |
| Cold start to listening¹ | about 0.5 s | about 7.2 s | 14x faster |
| Local tool call, p50 | 1.09 ms | 16.82 ms | 15x faster |
tools/list, p50 | 2.78 ms | 8.9 ms | 3x faster |
workitem list (20 items), p50² | about 686 ms | about 728 ms | about the same |
workitem list (20 items), response | 8.6 KB | 16.5 KB | 48% smaller |
| Install size | 1.7 MB, 1 file | 109.8 MB, 8,769 files | |
| Tool schemas sent to the client | 66.5 KB | 66.5 KB | identical |
¹ Includes the measuring loop's own overhead, so the Rust figure is an upper bound. ² Most of this is Plane itself, so Rust can't speed it up much. Measured with paced calls; the pacing delay is subtracted.
Rust doesn't reduce the tool schema cost, because the schemas are deliberately identical. Reproduce the latency and size numbers with bench/bench.py.
Tested against self-hosted Plane 1.4.2:
Linux and macOS builds are compiled and unit-tested in CI. The end-to-end testing above ran on Windows only.
Tool schemas, descriptions and PQL reference text come from plane-mcp-server (MIT). See LICENSE.