Firmament Open Brain
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Firmament Open Braincheck my open brain for context on Project Phoenix"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Firmament Open Brain
A shared "context brain" for the Firmament team, inspired by OB1 but rebuilt lean for Railway. It's an MCP (Model Context Protocol) server backed by Postgres: each person gets a private memory store that follows them across AI tools (Claude Desktop, Claude Code, claude.ai, Cursor, etc.). Memories are isolated per user — your token only ever sees your own memories.
How it works
One Railway service (this Node app) + one Railway Postgres.
Each user gets a personal token. Their MCP URL is
https://<host>/mcp/<token>.All memory reads/writes are scoped to the user that token resolves to. Tokens are stored hashed (SHA-256).
Search is Postgres full-text search with a substring fallback — no embedding API keys needed.
Related MCP server: LedgerMem MCP Server
MCP tools exposed
Tool | What it does |
| Store a memory (content + optional tags) |
| Search your memories by topic/keywords |
| List newest memories |
| Delete a memory by id |
Connecting a client
Claude Code:
claude mcp add --transport http openbrain https://<host>/mcp/<your-token>Claude Desktop / claude.ai: Settings → Connectors → Add custom connector → paste https://<host>/mcp/<your-token>.
Cursor: Settings → MCP → Add server, type http, same URL.
Then just talk: "remember that ..." / "what do you know about ...". A good habit is to start sessions with "check my open brain for context on ".
Admin (minting users)
Requires the ADMIN_TOKEN env var; pass it as a Bearer token.
# create a user (returns their token + MCP URL — shown only once)
curl -X POST https://<host>/admin/users \
-H "Authorization: Bearer $ADMIN_TOKEN" \
-H "Content-Type: application/json" \
-d '{"name": "Jack Wright"}'
# list users
curl https://<host>/admin/users -H "Authorization: Bearer $ADMIN_TOKEN"
# delete a user (and all their memories)
curl -X DELETE https://<host>/admin/users/<id> -H "Authorization: Bearer $ADMIN_TOKEN"Deploy (Railway)
Env vars on the app service:
DATABASE_URL— reference the Railway PostgresADMIN_TOKEN— long random string (admin API auth)DATABASE_SSL— set tofalseif connecting over Railway private networking
Deploy with railway up from this directory. Schema auto-creates on boot.
Security notes
The token lives in the URL. That's what makes hookup one-paste-easy, and it's acceptable for a small trusted team, but treat the URL like a password: don't share it, don't paste it in group chats.
Lost token → delete the user, mint a new one (memories are keyed to the user row, so deleting the user deletes their memories — export first if needed).
This server cannot be deployed
Maintenance
Related MCP Connectors
Persistent personal memory for AI assistants — save, search, and recall across every MCP client.
Shared, governed long-term memory for AI agents across tools and sessions via MCP and REST.
Your memory, everywhere AI goes. Build knowledge once, access it via MCP anywhere.
Person-owned AI memory that learns, not just stores — portable context for any MCP client.
Related MCP Servers
- AlicenseNot gradedqualityDmaintenanceShared memory for any MCP-compatible AI, enabling cross-platform knowledge persistence and retrieval so users' context, preferences, and project info follow them everywhere.3AGPL 3.0

LedgerMem MCP Serverofficial
AlicenseNot gradedqualityBmaintenanceEnables persistent memory storage and retrieval for MCP clients, allowing AI assistants to remember facts and context across conversations.351 npmMIT- AlicenseNot gradedqualityBmaintenanceProvides long-term memory for AI agents via MCP tools to store, recall, and delete memories, with per-user scoping and usage limits.AGPL 3.0

kumbukaofficial
FlicenseNot gradedqualityCmaintenanceEnables AI assistants to remember and apply shared team knowledge across sessions by storing, retrieving, and managing typed memory entries through MCP tools, including private scopes.1-