GitHub
GitHub’s official server lets AI read and manage code, issues and pull requests in your account. Use GitHub’s hosted version or run it locally with Docker.
Description from the maker (original English)
Fast single-binary server for Plane project management. Unofficial Rust port, 30 tools.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
PLANE_API_KEY, PLANE_WORKSPACE_SLUG, PLANE_BASE_URLValues marked secret are keys to your account. Never share them or paste them into a chat.
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Download the maker’s .mcpb file
The link goes to the maker’s own file; we do not host or repackage it. Open the file and Claude Desktop installs it.
Run this in your terminal
Fill in the empty values before running it.
Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
PLANE_BASE_URL envThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 9, 2026
The registry name was verified with the GitHub account ninerf, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
You need to fill in: PLANE_API_KEY, PLANE_WORKSPACE_SLUG
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.1.1) reached the registry 5 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need MCPB on your computer.
In the same category: GitHub, Desktop Commander, Cloudflare MCP
Servers in the same category from other makers, sorted by stars.
Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
GitHub’s official server lets AI read and manage code, issues and pull requests in your account. Use GitHub’s hosted version or run it locally with Docker.
MCP server for terminal commands, file operations, and process management
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
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.