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QuantumWars

Skill Graph MCP Server

by QuantumWars

Skill Graph

A Claude Code plugin that turns the skills and agents you already have into a graph you can query — from a session, in your browser, or in a desktop app.

It catalogues every agent and skill in the folders you point it at, counts which of them actually mention which others, scans your machine for projects that really have each one installed, and exposes all of it as MCP tools. Everything it knows comes from reading real files.

The graph

Click any node for what references it, what it references, which projects have it installed, and your own notes, ratings and tags:

A node in detail

Install

/plugin marketplace add QuantumWars/project-graphx
/plugin install skill-graph

Then, in any project you want a graph for:

/skill-graph:setup     # say where your skills and agents live — then offers to build
/skill-graph:build     # rescan, whenever the sources change
/skill-graph:view      # look at it, in your browser

/skill-graph:setup asks before building rather than just doing it, because a build with scanRoots set walks every scan root. Say yes and you go straight from nothing to a graph.

Each project gets its own graph. If you would rather have one catalogue shared by every project, run /skill-graph:setup-global instead — see One graph, or one per project.

/skill-graph:view needs no download — it serves the viewer from node, which the plugin already requires. /skill-graph:app opens the same viewer as a native desktop window instead, at the cost of a one-time ~280 MB Electron install.

Related MCP server: skills-mcp

Requirements

For

You need

Notes

The MCP tools

node 18+

The server ships pre-bundled. No npm install.

/skill-graph:build

python3 3.6+

Standard library only. On macOS this comes with the Xcode command line tools.

/skill-graph:view

nothing more

Same node as above.

add_repo

git

Only for importing an external repo's skills.

/skill-graph:app

npm + ~280 MB

One-time Electron install, on first launch only. Optional.

Running the tests

bun

Contributors only.

Windows is not supported for /skill-graph:build. The build commands invoke python3, which Windows Python installs do not usually provide (it is python or py). install_skill has the same dependency and fails after copying files, so it can leave a half-applied state. WSL works.

The desktop app's packaging script targets macOS arm64 only. On other platforms use /skill-graph:view, or run it unpackaged with npm start from app/.

One graph, or one per project

By default the data directory is <project>/.claude/graph, so two projects never see each other's graphs. That is usually what you want, and it is why nothing follows you between unrelated repos.

GRAPH_DATA_DIR overrides it. Set it and every project reads and writes the same directory:

dataDir = GRAPH_DATA_DIR  or  <project>/.claude/graph

/skill-graph:setup-global does that end to end — picks the location, finds every source on the machine, writes the config with absolute roots, sets the variable in ~/.claude/settings.json, and builds. It takes effect on the next restart, because an MCP server reads its environment at process start.

Sharing the directory shares the overlay too, so notes, ratings and tags become machine-wide rather than per-repo. If you want the same skills everywhere but not the same notes, do not set the variable — give each project a normal config whose source roots are absolute. Relative roots resolve against the project; absolute ones do not, so several projects can catalogue the same folders and still keep their own graphs.

Per-project graphs are never deleted by going global. Remove the variable and they are live again.

Where things live

Code ships with the plugin. Data belongs to the project:

<your project>/.claude/graph/
├── config.json        what to catalogue, what to scan   (you own this — commit it)
├── graph-data.json    the built graph                   (regenerated wholesale)
├── overlay.json       your notes, ratings, tags, edges  (survives rebuilds)
└── imported-repos/    shallow clones from add_repo

No graph data is ever written into the plugin directory, which is wiped on every reinstall. Two projects on the same machine get two independent graphs and never see each other's.

The one exception is Electron itself: /skill-graph:app installs it under the plugin's app/, so a plugin update means downloading it again. /skill-graph:view has nothing to reinstall, which is the main reason it is the default.

graph-data.json is rebuilt from scratch by every /skill-graph:build. Never edit it by hand — your edit will vanish. Everything you add through the tools goes to overlay.json, which builds never touch.

Configuring

.claude/graph/config.json:

{
  "sources": [
    { "repo": "my-project", "root": ".claude/agents", "kind": "agent" },
    { "repo": "my-project", "root": ".claude/skills", "kind": "skill" }
  ],
  "scanRoots": ["~/code"],
  "scanExclude": ["/node_modules/"]
}
  • sources — directories holding the agents and skills to catalogue. kind: "agent" for a folder of *.md; kind: "skill" for a folder of <name>/SKILL.md directories. Relative paths resolve against the project root. A missing root is skipped with a warning, not a crash.

  • scanRoots — trees searched for projects that have those skills installed. This is what fills in "who actually uses this". [] means scan nothing, and is honoured as written.

  • scanExclude — drop any path containing one of these substrings.

A project that owns a configured source is never counted as a user of its own catalogue. Without that, a repo cataloguing its own .claude/skills would report itself as a user of every skill in it, and every usage number would be inflated by one.

What the tools tell you, and what they don't

Edges are counted mentions. An edge exists because one file's text contains another node's name. That is a real, reproducible measurement — it is not a curated statement that two things belong together. A skill named after a common word collects edges by coincidence.

Usage is a filesystem fact. usedBy comes from checking whether the file is actually there. Absent means "not found under your scan roots", never "unused".

Categories are a guess. They come from a keyword heuristic at build time, which reads the name first and only falls back to the description when the name says nothing — a thing named python-testing is Python, a thing that merely mentions Python in passing is not. It is still a heuristic: it will file some things oddly and it says general when it cannot tell. Tags are hand-applied and mean what someone decided. Prefer tags.

Imported repos have no edges. add_repo extracts frontmatter only; cross-references are not computed for imports. Zero connections on an imported skill is a statement about the importer, not about the skill. This is also why importing a directory you already configured as a source is worse than useless, and why it is refused — see below.

When two things share a name

Two unrelated repos may each hold a code-reviewer, and both belong in the graph. So a lookup by name can be genuinely ambiguous, and the answer names the ids instead:

{ "error": "ambiguous", "candidates": ["myproj:agent:code-reviewer", "import:other:agent:code-reviewer"] }

Every tool that takes a node also accepts an id, so a candidate from that list can be passed straight back to resolve the tie — including install_skill and uninstall_skill, where picking the wrong one copies or deletes real files.

add_repo refuses a directory the build already catalogues. Both routes would reach the same files — the build writes them to graph-data.json, an import stores them in overlay.json, and the two are merged at read time — so every item under it would appear twice under one name, and no id could tell them apart because they are the same file. It stops before writing anything, naming the file that is already in the graph and ending "Nothing was imported."

Two different repos that happen to share a skill name are fine and still import; the check is on paths, not names.

The graph is a snapshot

It reflects the last build. Add a skill by hand, change a source, or install something outside these tools, and it is stale until you build again. install_skill and uninstall_skill re-scan themselves; nothing else does.

Development

bun install --frozen-lockfile   # exactly the versions CI and the bundle were built from
bun test                        # unit + end-to-end
bun run bundle                  # rebuild server/server.bundle.mjs after editing server/

bun.lock pins what the committed bundle is compiled from, and app/package-lock.json pins the Electron the desktop app was tested against. CI installs with --frozen-lockfile, so a dependency bumped without updating the lockfile fails the run instead of quietly shipping.

The viewer can be run directly, which is the fastest way to iterate on app/:

node server/viewer-server.js --data-dir <project>/.claude/graph

Re-bundle after any change under server/. .mcp.json runs the bundle, not the source, so an un-bundled edit is an edit that does not ship. The end-to-end suite launches the bundle exactly as Claude Code does and will fail if it is stale, and CI rebuilds it and fails if the committed copy differs.

bun run bundle also runs scripts/normalize-bundle.js, which replaces the __dirname literal the bundler freezes in at build time with a runtime expression. Without it the artifact would carry the absolute path of whoever built it, and two machines would never produce the same bytes — which is what makes the CI comparison possible at all.

Licence

MIT — see LICENSE.

A
license - permissive license
-
quality - not tested
A
maintenance

Maintenance

Maintainers
Response time
Release cycle
1Releases (12mo)
Commit activity

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