hooks — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited hooks (Hook) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
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<p> <a href="https://github.com/adelaidasofia/graph-autotagger-mcp/blob/main/LICENSE"><img alt="License" src="https://img.shields.io/github/license/adelaidasofia/graph-autotagger-mcp?color=blue"></a> <a href="https://github.com/adelaidasofia/graph-autotagger-mcp/stargazers"><img alt="GitHub stars" src="https://img.shields.io/github/stars/adelaidasofia/graph-autotagger-mcp?color=eab308"></a> <a href="https://github.com/adelaidasofia/graph-autotagger-mcp/commits/main"><img alt="Last commit" src="https://img.shields.io/github/last-commit/adelaidasofia/graph-autotagger-mcp"></a> <a href="https://github.com/adelaidasofia/graph-autotagger-mcp/issues"><img alt="Open issues" src="https://img.shields.io/github/issues/adelaidasofia/graph-autotagger-mcp"></a> <a href="https://pypi.org/project/adelaidasofia-graph-autotagger-mcp/"><img alt="PyPI version" src="https://img.shields.io/pypi/v/adelaidasofia-graph-autotagger-mcp?color=blue&label=pypi"></a> <a href="https://pypi.org/project/adelaidasofia-graph-autotagger-mcp/"><img alt="PyPI downloads" src="https://img.shields.io/pypi/dm/adelaidasofia-graph-autotagger-mcp?color=blue&label=downloads"></a> <a href="https://myceliumai.co"><img alt="Built by Mycelium AI" src="https://img.shields.io/badge/built_by-Mycelium_AI-15B89A"></a> </p>
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A FastMCP server that reads a pre-computed Obsidian knowledge graph and suggests wikilinks for your notes. Designed as a companion to graphify — run graphify to build the graph, then this MCP surfaces connections as you write.
| Tool | What it does |
|---|---|
suggest_links | Suggest wikilinks for a note based on token overlap with graph node labels |
check_god_nodes | Check which highly-connected nodes (top 20 by degree) are relevant to the note |
community_match | Find which graph communities the note most closely belongs to |
log_suggestion_decision | Log accepted/rejected/ignored decisions to a local SQLite database |
Open Claude Code, paste:
/plugin marketplace add adelaidasofia/graph-autotagger-mcp /plugin install graph-autotagger-mcp@graph-autotagger-mcp
After install, set GRAPH_JSON_PATH (see Environment variables below) and restart Claude Code, then ask:
"Suggest wikilinks for this note: [paste note content]"
<details> <summary>Legacy install</summary>
pip install fastmcp git clone https://github.com/adelaidasofia/graph-autotagger-mcp.git
cd graph-autotagger-mcp export GRAPH_JSON_PATH="~/vault/.graph/graph.json"Or pass it at registration time (see below).
python3 server.py claude mcp add graph-autotagger -s user -- \
env GRAPH_JSON_PATH="$HOME/vault/.graph/graph.json" \
python3 /path/to/graph-autotagger-mcp/server.py"Suggest wikilinks for this note: [paste note content]"
</details>
| Variable | Default | Description |
|---|---|---|
GRAPH_JSON_PATH | ~/vault/.graph/graph.json | Path to your graphify output |
AUTOTAGGER_DB | ~/.config/graph-autotagger/log.db | SQLite log for suggestion decisions |
The server loads graph.json once at startup and caches it in memory. Node labels are tokenized and matched against note content using token overlap scoring. God Nodes (top 20 by degree) get special treatment since connecting to them creates high-value cross-links.
The log_suggestion_decision tool lets you build a feedback dataset over time: accepted suggestions can be used to tune the relevance threshold; rejected ones reveal graph noise.
Expects the output format from graphify (networkx node_link_data):
{
"nodes": [{"id": "node-id", "label": "Node Label", "community": 0}],
"links": [{"source": "node-a", "target": "node-b"}]
}Note: networkx serializes edges under "links", not "edges".
Same author, same architecture pattern (FastMCP, draft+confirm on writes where applicable, vault auto-export, MIT):
This plugin sends a single anonymous install signal to myceliumai.co the first time it loads in a Claude Code session on a given machine.
What is sent:
slack-mcp)0.1.0)What is NOT sent:
Why: Helps the maintainer know which plugins people actually install, so attention goes to the ones that get used.
Opt out: Set the environment variable MYCELIUM_NO_PING=1 before launching Claude Code. The hook will skip the network call entirely. Already-pinged installs leave a sentinel at ~/.mycelium/onboarded-<plugin> — delete it if you want to reset state.
MIT
Built by Mycelium AI. Full install or team version at diazroa.com.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.