Self-hosted MCP memory server — 35 tools for persistent context across AI coding sessions. Runs on Docker with PostgreSQL + pgvector + Ollama.
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Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"engram-go": {
"command": "<see-readme>",
"args": []
}
}
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Every time you close your AI coding session, it forgets everything. The JWT library you chose. The expiry bug you spent an afternoon on. The pattern you explicitly rejected. Gone. Next session, the agent starts from zero and you start explaining.
No automated test available for this server. Check the GitHub README for setup instructions.
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Compact, efficient, and extensible long-term memory for LLM agents.
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Every time you close your AI coding session, it forgets everything. The JWT library you chose. The expiry bug you spent an afternoon on. The pattern you explicitly rejected. Gone. Next session, the agent starts from zero and you start explaining.
# Session start — before touching any code
memory_recall("session handoff recent decisions", project="myapp")
# After settling on a technical choice
memory_store(
"Chose RS256 over HS256: the API gateway needs to verify tokens without
holding the signing secret. HS256 would require distributing the key to
every service. Do not change this without updating the gateway config.",
memory_type="decision",
project="myapp"
)
Your memories stay on your machine.
Engram stores everything locally by design. Your PostgreSQL keeps every memory. Embeddings run locally via Ollama in local-only mode. Nothing leaves your machine unless you explicitly send it. Supported bootstrap modes:
docker-compose.local.yml.make up via docker-compose.yml. Requires ENGRAM_ROUTER_URL in .env (legacy LITELLM_URL fallback accepted, retained for backward compatibility; see issue #634). PostgreSQL defaults to the bundled postgres service; set POSTGRES_HOST / POSTGRES_PORT only when you are pointing Engram at an external database.Both setups share the same PostgreSQL backend, API contract, and tool set. Swap profiles without data loss or schema migration.
# Fresh-clone default: Local-only (zero external dependencies)
make init
docker volume create engram_pgdata
docker volume create ollama_ollama_storage
make build-postgres
docker compose -f docker-compose.local.yml up -d ollama
docker compose -f docker-compose.local.yml exec ollama ollama pull bge-m3
docker compose -f docker-compose.local.yml up -d
go run ./cmd/engram-setup --url http://127.0.0.1:8788
# Default home-network endpoint
# Hybrid profile checklist before `make up`:
# - `POSTGRES_PASSWORD` and `ENGRAM_API_KEY` are generated by `make init`
# - `ENGRAM_ROUTER_URL` (or legacy `LITELLM_URL`) points at your external router
# - `POSTGRES_HOST` / `POSTGRES_PORT` may be omitted for the bundled `postgres` service;
# set them only for an external PostgreSQL server
make init
make up
make setup
Finds what you mean, not just what you typed. BM25 keyword search and 1024-dimensional semantic vectors run simultaneously. Searching "database lock timeout" finds your note about "WAL mode contention under load" — no shared words, close meaning. When Ollama is unavailable, search degrades gracefully to BM25+recency. Your results never disappear because an external service went down.
Weights by recency automatically. Exponential decay at 1% per hour. Yesterday's decision outranks one from six months ago. Nothing is deleted; old memories step back. Six-month-old memories are still there if nothing more recent matches.
Surfaces connected memories without being asked. A knowledge graph links decisions to the bugs they caused and the patterns they require. Recall one; get its neighborhood. Store a bug report, store the architectural pattern that caused it, connect them with a causes edge. Now any query about the pattern automatically surfaces the bug — you don't have to remember to ask for both.
Stores documents, not just notes. `mem