The Graph

The Graph is a local knowledge graph your agents share over MCP: decisions made, approaches tried and failed, which agent owns which file. Agent B picks up where Agent A left off without rediscovering the same ground. Strictly opt-in.

Setup

Install and start Docker Desktop (enable Start at login).
In flock: Settings → Graph → Open the setup guide. Enable the graph and press Start the engine. Postgres + pgvector spin up in Docker, bound to localhost only.
Register the bundled MCP server in your agent tooling. For Claude Code:

claude mcp add --scope user flock-graph \
  -e FLOCK_KG_URL=postgresql://clarence:clarence@127.0.0.1:15432/clarence_kg \
  -- /Applications/Flock.app/Contents/MacOS/flock-mcp

The setup guide has ready-made snippets for OpenCode and Codex too. Verify with claude mcp list (look for flock-graph ✔).

Team hosting

Teams can share one centrally hosted graph instead of per-machine engines. Host any Postgres 14+ with the pgvector extension, load the schema from ~/.flock/graph/schema.sql, then point each teammate's flock at it: Settings → Graph → Team graph, paste the connection URL. Use the same URL as FLOCK_KG_URL when registering the MCP server (the snippets in Settings update automatically). Every teammate's agents then read and write the same decisions, attempts, and file claims.

How agents use it

Agents get five tools: kg.write_decision, kg.record_attempt, kg.claim_file, kg.query, and kg.related. flock exports each pane's identity into its environment, so graph writes are attributed to the right agent and workspace automatically, no prompting required. The sidebar shows live stats, the latest recorded knowledge, and warnings when two agents claim the same file.

Team Insights

The graph doesn't just remember; it keeps score. Open Team Insights from the bar-chart button on the Graph sidebar card to see what shared memory is saving you, over 7, 30, or 90 days:

Facts reused instead of re-derived. Every grounding hit is prior knowledge an agent got for free instead of burning tokens to rediscover.
Share of agent turns grounded in prior team knowledge.
Outcomes shipped: merged PRs, recorded automatically from your GitHub connection.
Spend per shipped PR: the cost curve that should bend down as the graph compounds.

Every graph event carries the person, agent, workspace, and (where set) org and team that produced it, so the numbers stay meaningful as more of your team points at the same graph. Organization-level scoping (sign in, land in your org, analytics per team) is being built on this same foundation and rolls out in upcoming releases.