SEC Ownership Graph

Every SEC ownership filing as one graph, keyed on CIK — so you can ask who moved first on a target, who operates as a coalition, and who really controls an issuer. Built on Neo4j. Every answer cites an SEC accession number, and abstains when the data doesn't support one.

Data: Schedule 13D/13G (beneficial ownership, 1994→present), Form 3/4/5 (insiders and directors), Form 13F (institutional holdings). Straight from EDGAR — no paid data vendor.

---

The demo in one question

"Which companies have had multiple activists show up recently — and who moved first?"

$ make demo

Activist convergence — 8 issuers:

  MNRO — MONRO, INC. (2 franchises within 96 days)
     2025-08-01  GAMCO INVESTORS, INC. ET AL 4.0%
     2025-11-05  ICAHN CARL C 14.79%
  ...

Ownership timeline — MONRO, INC.:
  2025-01-23  13G           DIMENSIONAL FUND ADVISORS LP (passive_index)
  2025-04-29  13G           BlackRock, Inc. (passive_index)
  2025-05-15  13G           NOMURA HOLDINGS INC (custodian)
  2025-08-01  13D     4.0%  GAMCO INVESTORS, INC. ET AL (activist)
  2025-11-05  13D   14.79%  ICAHN CARL C (activist)

First mover: GAMCO INVESTORS, INC. ET AL on 2025-08-01 at 4.0%
  → ICAHN CARL C followed 96 days later at 14.79%

Note what the graph does that a filings search cannot: it separates the two activists from the index money and the custodian inside the same filing type, and it puts them in order.

→ Full walkthrough: docs/demo_script_activist_desk.md (five questions, ~10 minutes, including what this cannot tell you.)

---

What is actually graph-native here

Three questions need a relationship followed to a depth the data decides — one declarative Cypher pattern, executed next to the data:

Question	Cypher	Why not SQL
Who ultimately controls this issuer?	(root)-[:CONTROLS|SAME_ENTITY_AS*1..N]->(target)	chain depth is unknown up front
Who operates as a coalition with X?	(seed)-[:CO_TARGETS*0..N]-(m)	the component is emergent, not a fixed join
Who bridges these two boards?	shortestPath((a)-[:SHARES_DIRECTOR*..N]-(z))	reachability, not "who sits on ≥2 boards"

Stated precisely, because overclaiming here loses technical audiences: SQL cannot express a single query whose traversal depth is decided by the data. A warehouse can still reach the same answers with a recursive CTE or by looping in application code. The advantage is one indexed declarative pattern next to the data — not that the answer is unobtainable elsewhere.

scripts/prove_graph_native_wins.py runs the graph traversal and the flat-SQL equivalent side by side and cross-checks that they agree (make prove).

---

Quickstart

# 1. Install
pip install -e ".[dev]"
cp .env.sample .env         # fill in NEO4J_PASSWORD

# 2. Point at a graph. Either build it (hours — downloads from EDGAR):
make build                  # dry-run: prints the full phased plan, writes nothing
make build-exec             # for real

# 3. Ask it things
make demo                   # the activist convergence screen
make prove                  # graph vs SQL, head to head
make serve                  # curated MCP tools over stdio

make serve exposes seven read-only tools to Claude Desktop or any MCP client (see .mcp.json) — activist_convergence, campaign_timeline, activist_coalition, ownership_snapshot, control_chain, board_interlock_path, get_secgraph_schema. Curated tools, not raw text2cypher: there is no Cypher passthrough and no write path, so the scrubs and thresholds that make the answers correct cannot be bypassed.

Requires Neo4j 5.x with GDS. A named database needs Enterprise or Aura; on Community, set NEO4J_DATABASE=neo4j.

---

How it is built

Layer 3  MCP server        curated read-only tools ─► Claude Desktop / any agent
Layer 2  Query core        traversals + evidence + abstain (transport-agnostic)
Layer 1  Reproducible DB   phased build, density gate, freshness manifest

make build runs the phases in order, aborting on the first failure: create the database → load the filer universe → stage and load Form 3/4/5 insiders → density GO/NO-GO gate (fail-closed: the build stops if the insider layer is too sparse to support the wins) → materialize the derived edges (SHARES_DIRECTOR, CONTROLS, SAME_ENTITY_AS, CO_TARGETS) → load 13D/13G and 13F. A successful run writes results/secgraph_freshness.json, which every served answer reports as its "as of" date.

schema/graph_schema.yaml is the single source of truth — 4 node labels, 9 relationship types. tests/unit/test_schema_consistency.py scans every .py file and fails the build if any Cypher references something undeclared.

Architecture detail: docs/reference_architecture_secgraph.md

---

Honest limits

Read these before demoing — they are part of what makes the rest credible.

• No prediction. The alpha question was tested and came back null. Efficient markets; 13Ds are public. This is a structural and temporal map, not a signal.
• No materiality data. No market cap, size or financials on any issuer, so results cannot be ranked by "does this matter." Bring your own universe filter. Largest known gap.
• Activist screens trade recall for precision. Gated to a curated franchise list; ungated detection is dominated by micro-cap founders crossing 5% and by filing-group artifacts (one manager filing through seven affiliated vehicles). First-time activists are missed by design.
• Only 13D/13G dates are a time series. Board and officer edges are a 2023–2026 keep-latest snapshot; 13F has a 2024 coverage step-up. Don't read trends into them.
• Control chains are a small-cap instrument. Every verified ≥50% chain in this dataset is a micro/nano-cap issuer. A real governance screen; not a large-cap feature.
• Board-interlock path existence is uninformative. Measured: every well-connected pair links within 4 hops. The named bridging director is the signal, not the connection.
• CIK-keyed only. Deliberately conservative — understates family/affiliate structure rather than inventing links through fuzzy name matching.
• Custodians and index funds are labelled, not deleted. They're excluded at query time so the underlying co-filing facts stay in the graph and the precision choice stays auditable.

Development

make test     # unit suite: fully mocked, no database needed
make check    # lint + tests, as CI runs them

License

MIT. SEC filing data is public domain.