mindgap

A local, org-roam-style knowledge graph for research and project knowledge: concepts, definitions, software, repos, Confluence pages, arXiv papers, people, teams. Nodes are markdown with [[wiki-links]] that auto-create edges; every node can carry outbound URLs. Curated by hand via CLI + web UI, and grown over time by autonomous agent loop sessions.

<p align="center"><img src="assets/demo.gif" alt="mindgap web UI — force-directed knowledge graph spreading into clusters" width="900"></p>

Stdlib-only Python 3.10 — no pip installs. Data lives in a single SQLite file.

Install

Pick one. All paths put mindgap (and mindgap-mcp) on your PATH and store data in ~/.mindgap (override with MINDGAP_HOME, or MINDGAP_DB for just the DB file).

pipx (recommended): pipx install git+https://github.com/grburgess/mindgap.git mindgap init # creates ~/.mindgap/mindgap.db and seeds it mindgap serve # web UI at http://localhost:8765

pip: pip install --user git+https://github.com/grburgess/mindgap.git mindgap init && mindgap serve # ensure ~/.local/bin is on PATH

From a clone (no install / development): git clone https://github.com/grburgess/mindgap.git && cd mindgap ./install.sh # self-locating: PATH + ~/.mindgap + seed mindgap serve

Claude Code plugin (skills + MCP)

/plugin marketplace add grburgess/mindgap
/plugin install mindgap

Registers the mindgap MCP server and the paper-to-mindmap, arxiv-explainer, papers-library, and loop-system skills. (After a pip/pipx install, register the MCP directly with claude mcp add mindgap mindgap-mcp; for a source checkout the repo's .mcp.json already points Claude Code at ./bin/mindgap-mcp.)

Where data lives

~/.mindgap/ — mindgap.db and snapshots/. MINDGAP_HOME relocates the whole dir; MINDGAP_DB points at a single DB file elsewhere.

CLI cheatsheet

mindgap add --title T [--id ID] [--type TYPE] [--body MD | --body-file F]
            [--tags a,b] [--url KIND=URL ...] [--by AGENT]
mindgap link SRC DST [--rel REL] [--weight W] [--by AGENT]
mindgap ingest FILE|-                       # bulk JSON ('-' = stdin)
mindgap find QUERY [--type T] [--tag T] [--json]
mindgap show ID [--json]                    # node + neighbors + urls
mindgap context QUERY [--depth 1]           # markdown digest (for agents)
mindgap rm ID
mindgap unlink SRC DST [--rel REL]
mindgap export [--out FILE]                 # JSON snapshot -> ~/.mindgap/snapshots/
mindgap stats
mindgap serve [--port 8765] [--no-open]

Web UI

mindgap serve opens a single-page graph viewer (dark editorial theme), in 2D or 3D:

• Force layout that spreads out instead of clumping — charge repulsion, a per-node collision force (2D), and tuned link distance keep nodes from overlapping, and the view auto-fits whenever the layout settles. Nodes are colored by type and sized by degree; hover a link to see its rel.
• Settings drawer (gear, top of the header) for live tuning, persisted to localStorage: a dark-theme picker (Editorial, Midnight, Graphite, Aubergine, Carbon), repulsion, link distance and strength, collision, link opacity, arrows, label mode, and the cluster controls below. "Reset to defaults" restores everything.
• Cluster feedback. Idea-communities are detected with multi-level Louvain — client-side, deterministic, no extra endpoint. Switch node coloring from type to community to surface them; in 2D each community also gets a translucent hull and a centroid label, and a legend (bottom-left) lists every community with its size — click one to isolate it and dim the rest. 3D conveys communities by color plus the legend.
• Labels in four modes (off / hover / hubs / always). In hubs mode the most-connected nodes stay labelled and the rest fade in as you zoom into a region (2D); 3D shows a name on hover.
• Search box and type/tag filter chips narrow the graph live; a stats line sits in the header.
• Click a node → sidebar with its markdown body (wiki-links are clickable), tags, outbound URLs (open Confluence/GitHub/arXiv in a new tab), and neighbors. Edit body/tags/urls, link to another node via a search picker, or delete — all inline.
• Focus mode (double-click a node) shows its local 1-hop graph; clicking nodes, wiki-links, or neighbors while focused spreads the view ring by ring (org-roam style), and Esc or "unfocus" resets. Selecting any node flies the camera to it and highlights its neighborhood.

The UI is vanilla JS with no build step, drawing force-graph/3d-force-graph, d3, marked, and dompurify from CDNs. Community detection and hull geometry live in web/cluster.js. (3D node labels are intentionally omitted: a CDN three global can't be version-matched to the one 3d-force-graph bundles, so 3D leans on color + legend + hover instead.)

MCP server

For agents, mindgap/mcp.py exposes the graph as an MCP server over stdio — stdlib-only (newline-delimited JSON-RPC 2.0, no pip deps). Source checkouts: registered in .mcp.json as ./bin/mindgap-mcp. pip/pipx installs: claude mcp add mindgap mindgap-mcp.

Ten tools wrap the same db layer as the CLI: mindgap_ingest (batch write), mindgap_add_node, mindgap_link, mindgap_unlink, mindgap_get_node, mindgap_find, mindgap_context, mindgap_stats, mindgap_export, mindgap_remove_node. Unlike the raw CLI, the write tools validate at the call boundary — mindgap_ingest rejects the whole payload (no partial commit) if any edge endpoint isn't in the DB or the payload, mindgap_link refuses to auto-stub a missing endpoint, created_by is required, and writes return the persisted rows so a caller can't claim a write that didn't land.

Agent loops

The graph is designed to be fed by recurring autonomous sessions that scan Confluence, GitHub, and arXiv. The protocol — read context first, ingest JSON with provenance (created_by, source URLs), wiki-link into the existing graph, export at session end — is defined in AGENTS.md. Sessions can drive the graph via the CLI or the MCP tools above (the MCP's validation makes it the safer path for unattended writes).

Knowledge loops (arXiv search → graph)

The bundle ships self-improving loop templates that sweep arXiv for a topic and ingest findings into your graph with evidence-backed links — driven by the loop-system skill.

List what's available and scaffold one: mindgap loop list mindgap loop new arxiv-weekly --name my-watch --topics "your research area"

Then just tell Claude (in the project where you scaffolded it): "continue the my-watch loop"

Bundled templates:

• arxiv-weekly — recurring weekly 7-day arXiv sweep; tags every find, self-tunes its query strategy each pass. Schedule it unattended via the generated CRON.md (launchd/cron).
• paper-discovery — one-shot batch discovery of papers for a topic.
• paper-links — densify the graph by finding missing links between existing papers.
• implementation-ideation — mine the graph's growing connections for buildable ideas, then adversarially refute the infeasible ones; only vetted ideas (each with an MVP sketch) are ingested.
• author-graph — build a person-node graph of the researchers behind the work, with their resolved GitHub / homepage / Scholar links and co-author connections.

Share a loop you've built (strips your accumulated state): mindgap loop export my-watch # -> ./my-watch-template/ mindgap loop import ./my-watch-template --name their-watch --topics "..."

Prompts you can hand to Claude directly (once the plugin is installed):

• "set up an arxiv-weekly loop watching <your topics> and run the first pass"
• "continue the <name> loop"
• "export the <name> loop as a template I can share"
• "ideate implementations from the growing connections in my <name> graph, and refute the ones that aren't feasible" (implementation-ideation)
• "build a graph of the authors doing <your topics> work, with their github pages" (author-graph)

Paper explainers

The bundled arxiv-explainer skill turns a paper into a richly animated, narrated HTML explainer — figures extracted from the PDF, a self-contained dark theme — and ingests it into your graph. Just tell Claude explain <arXiv link> (or point it at a local PDF).

Import a Papers library

Mine your Papers (ReadCube) reference library into the graph: export it to BibTeX or RIS (Papers → Settings → Export) and tell Claude:

"import my Papers library from <path-to-export.bib>"

The bundled papers-library skill parses the export (stdlib, no deps), ingests each paper as a node (deduped against the graph, evidence-linked), discovers related papers not yet in your library, and seeds ideas — handing off to the paper-links / implementation-ideation loops for depth.

Schema overview

Two tables:

• nodes(id, title, type, body, tags, urls, confidence, created_by, created_at, updated_at) — id is a kebab-case slug; tags/urls are JSON arrays; types: concept|definition|software|repo|page|paper|person|team|stub.
• edges(src, dst, rel, weight, created_by, created_at) — rels: relates_to|defines|implements|depends_on|cites|part_of|mentions.

[[wiki-links]] in a body sync to mentions edges automatically, creating stub nodes for missing targets. Upserts merge: scalar fields replace, tags/urls union.

Export & snapshots

The DB is gitignored; history is kept as JSON snapshots:

mindgap export                # ~/.mindgap/snapshots/<utc>.json
mindgap export --out my.json

Commit snapshots for a durable, diffable record; re-ingest one with mindgap ingest FILE to restore.

Development

python3 -m mindgap ...                 # run CLI from repo without install
python3 -m unittest discover tests

License

MIT — see LICENSE.