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FastMCP server for surgical queries against a vault knowledge graph (NetworkX no

adelaidasofia/graph-query-mcp
2authSTDIOregistry active
Summary

If you've built a knowledge graph from your Obsidian vault using NetworkX, this server lets Claude query it surgically instead of dumping 50K lines of graph data into context every time. It loads your graph.json once at startup and exposes seven tools: fuzzy node search, neighbor traversal with configurable hop depth, shortest path finding, degree-ranked top nodes, subgraph extraction around concept clusters, detailed node metadata, and community detection lookups. Supports dual graphs if you maintain separate personal and team vaults. Pairs naturally with the graphify skill from ai-brain-starter, though any NetworkX node-link JSON works. Query latency under 50ms, all in-memory, no external services.

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graph-query-mcp

License GitHub stars Last commit Open issues PyPI version PyPI downloads Built by Mycelium AI

Surgical queries against an Obsidian / vault knowledge graph. Loads a graph.json (NetworkX node-link format) once at startup and answers targeted questions without making Claude read a 50K-line graph report.

Designed to pair with graphify (the graph-building skill in ai-brain-starter), but the server accepts any graph in NetworkX node-link JSON. Supports up to two scopes (primary + secondary, e.g. personal + team).

Why use this

If you've already run graphify on a vault, you've got a graph.json and a GRAPH_REPORT.md. Reading the full report into Claude burns thousands of tokens for every question. This MCP loads the graph once at startup, answers in <50ms, and never spills the whole graph into context.

Tools

ToolWhat it does
search_nodes(query, scope, limit)Fuzzy match against node names. Returns node IDs ranked by exact / starts-with / contains.
get_neighbors(node_id, scope, max_hops, limit)Connected nodes within N hops, sorted by degree.
find_path(source, target, scope)Shortest path between two concepts. Auto-fuzzy-matches both ends.
get_top_nodes(scope, n)Highest-degree nodes (the "god nodes").
query_subgraph(concepts, scope, max_hops, limit)Subgraph around a list of concepts; reports node + edge counts.
get_node_info(node_id, scope)Full metadata + top neighbors for one node.
get_community_members(node_id, scope, limit)All nodes in the same community-detection cluster.

Scope defaults to personal; pass scope="onde" (or whatever secondary scope name you've configured) for the second graph.

Configuration

Two env vars, both optional:

Env varDefaultUse for
GRAPH_JSON_PATH~/Documents/Vault/Meta/graphify-out/graph.jsonPrimary graph (the personal scope)
SECONDARY_GRAPH_JSON_PATH~/Documents/Vault/Team/Meta/graphify-out/graph.jsonSecondary graph (the onde scope, historical name)

ONDE_GRAPH_JSON_PATH is also accepted as a backward-compat alias for SECONDARY_GRAPH_JSON_PATH.

If a path doesn't exist at startup, the server logs a warning and the tools return a friendly error when that scope is queried. The server still starts — a missing secondary graph never blocks the primary.

Install

Open Claude Code, paste:

/plugin marketplace add adelaidasofia/graph-query-mcp
/plugin install graph-query-mcp@graph-query-mcp
Legacy install
git clone https://github.com/adelaidasofia/graph-query-mcp.git ~/.claude/graph-query-mcp
cd ~/.claude/graph-query-mcp
pip3 install --break-system-packages -r requirements.txt

Register in your project .mcp.json:

{
  "mcpServers": {
    "graph-query": {
      "type": "stdio",
      "command": "fastmcp",
      "args": ["run", "/Users/YOU/.claude/graph-query-mcp/server.py"],
      "env": {
        "GRAPH_JSON_PATH": "/path/to/your/vault/Meta/graphify-out/graph.json"
      }
    }
  }
}

Restart Claude Code, then claude mcp list should show graph-query connected.

Generating the graph

This MCP doesn't build the graph; it queries one. Use graphify (a skill in ai-brain-starter) to produce a graph.json from your vault, or any other NetworkX-compatible builder. The expected format is the output of networkx.node_link_data(G).

Verification

python3 tests/integration/test_smoke.py
# expected: PASSED — graph-query-mcp smoke (4 steps green)

Architecture

FastMCP, stdio transport, Python 3.10+. Graphs are loaded once at startup and cached in memory. No daemons, no listeners, no external services. NetworkX in-memory for query primitives.

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
  • apollo-mcp — Apollo.io CRM + sequences
  • google-workspace-mcp — Gmail / Calendar / Drive / Docs / Sheets
  • substack-mcp — Substack writing + analytics
  • parse-mcp — markitdown / Docling / LlamaParse router
  • luma-mcp — lu.ma events
  • graph-autotagger-mcp — wikilink suggestions from the same graph format

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. See LICENSE.

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Configuration

GRAPH_JSON_PATH*

Absolute path to your graphify-out/graph.json

Categories
Documents & KnowledgeData & Analytics
Registryactive
Packagehttps://github.com/adelaidasofia/graph-query-mcp/releases/download/v0.1.0/graph-query-mcp.mcpb
TransportSTDIO
AuthRequired
UpdatedMay 20, 2026
View on GitHub

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