Myco Brain

Persistent, source-traceable memory for AI agents — self-hosted on your own Postgres, with no API keys required to run.

• Source-traceable. Every fact traces to the document it came from (brain_why) — no trust-me summaries.
• Trust that compounds. Independent corroboration raises a fact's confidence; a contradiction supersedes it — kept and audited, never silently overwritten.
• Keyless & local-first. Full-text + semantic search and the knowledge graph all run with zero hosted dependency — add an Anthropic key only for the most accurate graph.
• Yours. Apache-2.0, plain Postgres tables, 13 MCP tools. Works with Claude, Cursor, Windsurf, Continue, Zed.

Who it's for: dev teams running agents that need one shared memory · agencies needing hard per-client isolation · anyone who wants their assistant to remember across sessions — import your ChatGPT / Claude history (from your data export) and your AI knows you on day one.

Built solo by a growth marketer — not a career engineer — directing AI coding agents over ~3 months. How it was built ↓

The usual fix for agent amnesia — letting an LLM maintain its own memory — fills it with duplicates, hallucinated summaries, and confident answers nobody can trace. Myco Brain is built on the opposite contract:

The LLM proposes. Deterministic rules decide what becomes a fact. You set the bar — from corroboration-gated auto-promotion (the default) to strict human review of every fact (BRAIN_REQUIRE_HUMAN_REVIEW=1).

Claude, Cursor, Windsurf, Continue, Zed, and custom agents all share one memory backed by your own Postgres.

⭐ If the trust model resonates, a star helps others find it.

# 1. Boot the stack (Postgres + MCP server + extraction worker)
git clone https://github.com/thegoodguysla/myco-brain.git && cd myco-brain
docker compose up -d

# 2. Give your agent a memory — point it at any repo or folder
#    (no env needed: it finds the quickstart stack on localhost)
npx -y -p @mycobrain/mcp-server mycobrain-ingest github:your-org/your-repo

# 3. Connect your client (one-liner below), then ask across sessions:
#    "what did we decide about auth, and where is that documented?"
#    → answered from your docs, with the source cited.

[!TIP] Zero API keys, all the way down. Full-text search, semantic search (local embeddings), and the knowledge graph (local extraction) all run with no hosted dependency. Add an Anthropic key only if you want the most accurate graph.

MCP-native by design — your agent knows when to use memory, not just how. Most MCP servers expose tools and hope the model calls them. Myco ships a usage contract over MCP's instructions channel: the moment it connects, your agent knows to pull context before a task, save durable decisions, and cite sources with brain_why — no per-project prompting. Tune the policy in one copy-paste block: Teach your agent to use it well.

Quick links: 10-minute quickstart · Teach your agent to use it well · The trust engine · Benchmark — run it yourself · Run every proof · Who it's for · Environment variables · Architecture · Roadmap · Cloud waitlist

Memory that gets more trustworthy (compounding confidence)

Most agent memory overwrites facts silently. Myco Brain compounds them:

• An independent source agreeing with a fact raises its confidence (damped noisy-OR — ten chunks of one document corroborate nothing; only distinct sources count).
• A confident contradiction on a single-valued relationship (who you work for, where something is located) supersedes the old fact: it's closed and weakened — kept, never deleted — with the supersession recorded in an audited claims ledger.
• Ask brain_why about any fact and you get its distinct source count (per relationship, not per mention), its confidence trend over time ("0.8 → 0.86"), and any superseded history. Contradictions stay visible. Your memory can't gaslight you.

works for → Halcyon Labs           0.55  [SUPERSEDED — kept, not deleted]
works for → Driftwood Analytics    0.90  [ACTIVE]
claims ledger: old fact superseded_by → new fact (audited)

Proof: npm run test:compounding — the full lifecycle runs against a live database in seconds, no LLM required.

The schema evolves with your data (dynamic schema)

• The extraction worker notices entity kinds and relationship types your catalog doesn't have yet and proposes them (brain_stats: "Brain proposed 3 new types from your data").
• Promotion is yours by default — or opt into auto-promotion for types corroborated across enough distinct source documents (BRAIN_SCHEMA_AUTO_PROMOTE=1), counted per document, not per mention, so two documents passed back and forth can't manufacture consensus. One chatty document can never promote anything.
• A promoted type stays scoped to the workspace that earned it — one client's vocabulary never leaks into another's catalog (see per-client isolation).

Proofs: npm run test:dynamic-schema, npm run test:schema-promotion.

You pick the trust dial:

When something is waiting on you — novel types in default mode, or everything in strict mode — review it from the command line:

mycobrain review                 # list pending entities, relationships, types
mycobrain review approve <id>    # promote it into the graph
mycobrain review reject  <id>    # reject it (kept and audited, never deleted)

Proof: npm run test:review — approving actually lands the entity / edge / type in the canonical graph; rejecting never does.

Private memories, shared knowledge

Multi-agent teams get real isolation: documents marked private are readable only by the agent that created them — enforced in every read tool, on top of workspace row-level security. Workspace memory stays shared. Proof: npm run test:sharing (a two-agent visibility matrix). Like workspace isolation, it binds only under the least-privilege brain_app role (security note).

One isolated workspace per client — built for agencies

Put each client in their own workspace, share one agency-wide playbook, and the guarantee you sell is Postgres row-level security — a session scoped to Client A cannot return Client B's rows. The agency starter kit provisions it (one command) and ships the least-privilege DB role that makes the isolation actually bind. Proof: npm run test:agency — Client A sees zero of Client B's facts.

[!IMPORTANT] Isolation binds only under the least-privilege role. RLS does not constrain a Postgres superuser, and the zero-config quickstart's default brain role is a superuser (fine for a single-workspace self-host — there's nothing to isolate). Before you put more than one client in one database, run the app as the NOSUPERUSER brain_app role the agency kit ships; mycobrain-doctor flags a superuser connection. Multi-tenant isolation is a guarantee of brain_app, not of the default quickstart role.

Query over HTTP (read-only)