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Description from the maker (original English)
Indexed C/C++ code navigation for AI agents — GNU Global (gtags) lookups over MCP, not grep scans.
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.
GTAGS_MCP_ROOT, GTAGS_MCP_AUTO_SETUPYou need
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"gtags": {
"command": "uvx",
"args": [
"mcp-gtags-server"
],
"env": {
"GTAGS_MCP_ROOT": "your-value",
"GTAGS_MCP_AUTO_SETUP": "your-value"
}
}
}
}Run this in your terminal
claude mcp add gtags --env GTAGS_MCP_ROOT=your-value --env GTAGS_MCP_AUTO_SETUP=your-value -- uvx mcp-gtags-serverFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"gtags": {
"command": "uvx",
"args": [
"mcp-gtags-server"
],
"env": {
"GTAGS_MCP_ROOT": "your-value",
"GTAGS_MCP_AUTO_SETUP": "your-value"
}
}
}
}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.
Paste into .vscode/mcp.json in your project
{
"servers": {
"gtags": {
"type": "stdio",
"command": "uvx",
"args": [
"mcp-gtags-server"
],
"env": {
"GTAGS_MCP_ROOT": "your-value",
"GTAGS_MCP_AUTO_SETUP": "your-value"
}
}
}
}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.
GTAGS_MCP_ROOT envGTAGS_MCP_AUTO_SETUP 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 8, 2026
The registry name was verified with the GitHub account harshithsunku, 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.
The registry does not list a required key, though some servers ask you to sign in on first use.
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 (2.0.0) reached the registry 2 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) 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:★ 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
Cloudflare MCP servers
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.
Stop letting your AI agent grep. Give it an index.
mcp-name: io.github.harshithsunku/mcp-gtags-server
# If you don't have uv yet (one-time, no sudo):
curl -LsSf https://astral.sh/uv/install.sh | sh
{ "mcpServers": { "gtags": { "command": "uvx", "args": ["mcp-gtags-server"] } } }
*One user-level config entry, no sudo, no pre-installed anything — the whole toolchain installs itself into user space on first use, and every repo you open is served automatically.*
📖 [Full documentation](https://harshithsunku.github.io/mcp-gtags-server/) — install for every client, the tool reference, output format, kernel features, configuration and troubleshooting.
Every AI coding agent — Claude Code, Cursor, Codex, you name it — answers *"where is this function defined?"* the same way: grep the entire tree. On a million-line C/C++ codebase that's a full scan per question, and the output is a firehose: every comment, string literal, and unrelated match, dumped straight into the model's context window.
mcp-gtags-server replaces those scans with indexed lookups powered by GNU Global (gtags) — the same tags engine kernel and systems developers have trusted for decades — exposed to agents over the Model Context Protocol. Built for the codebases LSP-based tools can't handle: kernel-scale C/C++, trees that don't currently compile, machines you can't sudo on.
#ifdef guard stacks with .config filtering, macro-generated symbols (sys_read → its SYSCALL_DEFINE3 site) that no other tagging tool resolves, and definitions the parser misses recovered from their EXPORT_SYMBOL site via ctagsMeasured on a full Linux kernel checkout — 65,163 C/C++ files, 37.1 million lines — warm page cache:
| Question an agent asks | grep -rn | gtags (this server) | Context consumed |
|---|---|---|---|
Where is tcp_v4_rcv defined? | 1.40 s | 0.01 s | 8 lines → 1 line |
Where is kmalloc defined? | 1.62 s | 0.01 s | 7,873 lines → 5 lines |
Who references kmalloc? | 1.62 s | 0.10 s | 7,873 noisy lines → 2,744 real sites (or a ranked per-file summary) |
Show me tcp_v4_rcv's implementation | *read a 3,500-line file* | `get_symbol_body` | exactly the 271-line function |
Who calls ext4_mark_inode_dirty? | 245 raw match lines | `find_callers` | 62 deduped caller functions, with counts |
Where is sys_read *really* defined? | *no answer — the name is macro-generated* | 0.03 s | fs/read_write.c SYSCALL_DEFINE3(read, ...), flagged resolved_via |
Where is mutex_lock defined? | 24,774 noisy match lines | 0.2 s | kernel/locking/mutex.c:314 — recovered via EXPORT_SYMBOL + ctags after gtags' parser derails on it |
Does ksys_read ever reach rw_verify_area? | *N rounds of grep + reading* | 0.6 s | the shortest call chain, with every call site's file:line |
Every mutex_lock call in fs/ext4? | 22,905 tree-wide match lines | 0.01 s | find_references(path_prefix="fs/ext4"): the 18 real sites |
One-time index build: 66 s for the whole kernel. Incremental refresh after edits: well under a second. Reproduce it yourself with scripts/benchmark.sh:
./scripts/benchmark.sh /path/to/linux tcp_v4_rcv kmalloc ext4_readdir
The speed is nice. The real win is precision: an agent that gets 5 exact lines instead of 7,873 noisy ones keeps its context window for actual reasoning.
And the answers are *measured*, not assumed: CI runs a 64-case golden eval against pinned kernel v6.16 on every push — currently 100% recall, 100% precision@1 across definitions, macro resolution, export recovery, references, callers, callees, definition bodies, #ifdef guards, and reachability, covering all 8 tools. The full methodology, numbers, and honest limitations live in docs/capability.md.
Add the server once, at user level, and you're done — no installer, no pre-installed gtags, no per-repo setup. The only prerequisite is uv (or use Option B, which installs it for you).
# Claude Code (once per device, all repos):
claude mcp add --scope user gtags -- uvx mcp-gtags-server
// Cursor (~/.cursor/mcp.json), or any MCP client's global settings:
{ "mcpServers": { "gtags": { "command": "uvx", "args": ["mcp-gtags-server"] } } }
Or click the Cursor one-click install badge at the top of this page.
On the very first tool call the server bootstraps everything else by itself: GNU Global (prebuilt user-space binaries — no compiler, no sudo), universal-ctags, and Pygments, all into ~/.gtags-mcp. While that one-time install runs (a few seconds on most platforms), tool calls return a *"toolchain is being installed — retry shortly"* status instead of failing. Opt out with --no-auto-setup or GTAGS_MCP_AUTO_SETUP=0.
The prebuilt Linux binaries run on any distro with glibc ≥ 2.28 (RHEL/Rocky 8+, Ubuntu 18.10+, Debian 10+). On older hosts — or if a downloaded binary fails its post-install execution check — setup automatically compiles GNU Global from source instead, which only needs make and a C compiler.
The plugin bundles this server, a "C/C++ code navigation" skill that tells the agent which tool answers which question, and two slash commands (/gtags:impact, /gtags:explain). Installing it registers the MCP server for you — there is no config file to edit.
| Client | Install |
|---|---|
| Claude Code | /plugin marketplace add harshithsunku/mcp-gtags-server then /plugin install mcp-gtags-server@mcp-gtags-server |
| Codex | codex plugin marketplace add harshithsunku/mcp-gtags-server, then install it from the Plugins Directory in the ChatGPT desktop app |
| Cursor | Loads Agent Plugins 1.0.0, but installs only from the Cursor Marketplace or a team marketplace — until this plugin is listed there, use the one-click badge or Option A |
Install one way, not both. A plugin *and* a manual entry run two servers,
and the agent sees every tool twice. Switching to the plugin? Remove the
manual entry first (
claude mcp remove gtags).
One command. No sudo. Works everywhere — restricted corporate machines, containers, build servers:
curl -fsSL https://raw.githubusercontent.com/harshithsunku/mcp-gtags-server/main/scripts/install.sh | bash
Everything lands in your home directory — the server (via uv), GNU Global, universal-ctags, and Pygments (in ~/.gtags-mcp). When it finishes, a shared background HTTP server is running that every client and IDE window on the machine can point at (http://127.0.0.1:8383/mcp), and the exact client configuration is printed to your console.
Re-run the same command any time:
Available with any install, in clients that support MCP prompts (Claude Code, Cursor). They cost no tool-schema context:
| Command | What it runs |
|---|---|
/gtags:impact [git_ref] | git diff → the changed functions → find_callers on each → callers ranked by risk |
/gtags:explain | definition (+ #ifdef variants) → body → callers → a short explanation |
However you install it, one user-level entry serves every repo you open — 20 repos need zero extra installs and zero extra config. Each tool call resolves its project root down this ladder:
project_root argument on the tool call (agents pass this to target any tree)--root flag / GTAGS_MCP_ROOT env varroot in a config file *(note: pinning a root here defeats multi-repo)*project_root. Roots exist only for clients on protocol revisions up to 2025-11-25: the 2026-07-28 revision deprecated them, so those clients skip this step (stdio servers still resolve through step 5; on the shared HTTP server, agents pass project_root).git/GTAGS — this is why stdio servers spawned by Claude Code/Cursor inside a repo just workStep 5 can be switched off with --no-cwd-fallback / GTAGS_MCP_CWD_FALLBACK=0 (the plugin sets it): the tools then ask for project_root instead of indexing whatever directory the server happens to run in. Plugin clients launch the server from the plugin's own folder, which is never your project.
That's it. No indexing step, no configuration. Ask your agent *"who calls tcp_v4_rcv?"* — the first query in any repo builds that repo's index automatically, and every query after that is answered in milliseconds. Run mcp-gtags-server doctor any time to see what the server detects, or mcp-gtags-server config to re-print the client configuration.
Background server details (network access, port, lifecycle)
The installer runs mcp-gtags-server --transport http --host 127.0.0.1 --port 8383 in the background (pid: ~/.gtags-mcp/server.pid, log: ~/.gtags-mcp/server.log). Environment overrides for the installer:
| Variable | Default | Meaning |
|---|---|---|
GTAGS_MCP_PORT | 8383 | HTTP port |
GTAGS_MCP_HOST | 127.0.0.1 | Bind address — set 0.0.0.0 to reach the server from other devices at http:// :8383/mcp |
GTAGS_MCP_NO_SERVER | unset | 1 = don't start a background server |
Security note: the HTTP endpoint is unauthe
Only the beginning is shown; read the rest in the repo