FastMCP server for Obsidian wikilink suggestions from a pre-computed knowledge g
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Summary
Built for Obsidian users who want algorithmic wikilink suggestions from an existing knowledge graph. You run graphify separately to generate graph.json from your vault, then this server loads it into memory and exposes four tools: suggest_links does token overlap scoring between note content and graph node labels, check_god_nodes filters the top 20 highest-degree nodes for relevance, community_match tells you which graph clusters your note belongs to, and log_suggestion_decision writes accept/reject feedback to SQLite so you can tune thresholds over time. The graph stays read-only in the server; all mutations happen in your editor. Pairs naturally with vault-sync-mcp and graph-query-mcp from the same author if you're building a full MCP-driven note pipeline.
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one prompt install →graph-autotagger-mcp
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.
Tools
| 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 |
Install
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]"
Legacy install
pip install fastmcp
-
Clone:
git clone https://github.com/adelaidasofia/graph-autotagger-mcp.git cd graph-autotagger-mcp -
Set the path to your graph.json:
export GRAPH_JSON_PATH="~/vault/.graph/graph.json"Or pass it at registration time (see below).
-
Self-test:
python3 server.py -
Register with Claude Code:
claude mcp add graph-autotagger -s user -- \ env GRAPH_JSON_PATH="$HOME/vault/.graph/graph.json" \ python3 /path/to/graph-autotagger-mcp/server.py -
Restart Claude Code, then ask:
"Suggest wikilinks for this note: [paste note content]"
Environment variables
| 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 |
How it works
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.
graph.json format
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".
Related MCPs
Same author, same architecture pattern (FastMCP, draft+confirm on writes where applicable, vault auto-export, MIT):
- slack-mcp - multi-workspace Slack
- imessage-mcp - macOS iMessage
- whatsapp-mcp - WhatsApp via whatsmeow
- google-workspace-mcp - Gmail / Calendar / Drive / Docs / Sheets
- apollo-mcp - Apollo.io CRM + sequences
- substack-mcp - Substack writing + analytics
- luma-mcp - lu.ma events
- parse-mcp - markitdown / Docling / LlamaParse router
- rescuetime-mcp - RescueTime productivity data
- graph-query-mcp - vault knowledge graph queries
- investor-relations-mcp - seed-raise pipeline tracker
- vault-sync-mcp - bidirectional vault sync
Telemetry
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:
- Plugin name (e.g.
slack-mcp) - Plugin version (e.g.
0.1.0)
What is NOT sent:
- No user identifiers, names, emails, tokens, or API keys
- No file paths, message content, or anything from your work
- No IP address is stored after dedup processing
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.
License
MIT
Built by Mycelium AI. Full install or team version at diazroa.com.
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Try For Free →Your agent targets a perfect 10 Code Health score. Deterministic. Every commit.
Try For Free →Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
one prompt install →Configuration
GRAPH_JSON_PATH*Absolute path to your graphify-out/graph.json
Categories
Registryactive
Packagehttps://github.com/adelaidasofia/graph-autotagger-mcp/releases/download/v0.1.0/graph-autotagger-mcp.mcpb
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UpdatedMay 20, 2026
