librechat-mnemonic
Enables automatic, project-scoped long-term memory for LibreChat conversations by recalling relevant memories before each turn and writing durable facts after each turn. It integrates via a proxy that resolves project context from MongoDB and exposes MCP tools for explicit memory management.
README
librechat-mnemonic
Automatic, project-scoped long-term memory for LibreChat, backed by a local mnemonic MCP server.
Chats inside a LibreChat project recall that project's memories and write new ones back to it. Chats outside a project use the global pool. It is on by default and can be turned off per chat, per user, or entirely.
Nothing is forked or patched. This runs as one container alongside LibreChat.
What it does
- Recalls before every turn. Relevant memories are retrieved and injected as context before the model is called. This does not depend on the model deciding to call a tool.
- Writes after every turn. Durable facts are extracted from the exchange and stored, with duplicates detected and skipped.
- Scopes by LibreChat project. A chat in the "Home Network" project reads and writes memories stamped with that project. Memories live in one global vault, partitioned by project, so nothing is siloed unless you want it to be.
- Stays out of the way.
/memory offin any chat, and that conversation stops recalling and storing. - Exposes tools too. An MCP endpoint lets agents search, correct, and forget memories explicitly when the automatic path is not enough.
How it works
browser → LibreChat → librechat-mnemonic → your model provider
│ │
│ ├── stdio ──→ mnemonic ──→ vault (markdown + git)
│ │
└──── mongo ────┘ (read-only: conversation → project)
LibreChat has no server-side plugin API, so the integration hangs off two supported extension points:
- Custom endpoints with header placeholders. LibreChat resolves
{{LIBRECHAT_USER_ID}}and{{LIBRECHAT_BODY_CONVERSATIONID}}into request headers. That is how the proxy knows who is asking and in which conversation. - MCP servers over streamable HTTP, for the explicit tool surface.
The project is not in the request. LibreChat's ALLOWED_BODY_FIELDS is conversationId, parentMessageId, messageId and nothing else, so the proxy resolves it itself: conversations.chatProjectId → chatprojects.name, read from the same MongoDB LibreChat already uses. Its own collections are never written to.
Why a proxy and not just MCP tools
Because "automatic" and "the model decides" are different things.
LibreChat's own memory feature can be driven externally: with memory.agent.enabled unset, every run loads memories from the MemoryEntry collection and injects them with no tool call involved. But that lookup is keyed by user id alone. There is no conversation or project dimension in the schema, and the load happens inside LibreChat before anything external runs. So that channel gives automatic but user-global.
The only place that can see the project is the request path. Hence a proxy.
The MCP tools are still worth having, they just do a different job: correcting a memory the extractor got wrong, or searching for something the recall query missed.
Requirements
- LibreChat v0.8.7 or later (projects landed in 0.8.7; header placeholders are older)
- Access to LibreChat's MongoDB
- An embedding provider for mnemonic: a local Ollama, or an OpenAI or Gemini key
Quick start
Add the service to your LibreChat compose file. See docker-compose.example.yml for the annotated version.
services:
librechat-mnemonic:
image: ghcr.io/claudedowling/librechat-mnemonic:latest
restart: unless-stopped
environment:
LIBRECHAT_MONGO_URI: mongodb://mongo:27017/LibreChat
UPSTREAMS: >-
[{"name":"openai","baseUrl":"https://api.openai.com","api":"openai"}]
OLLAMA_URL: http://ollama:11434
volumes:
- mnemonic-vault:/vault
- mnemonic-projects:/projects
networks: [librechat-network]
Then point LibreChat at it in librechat.yaml:
endpoints:
custom:
- name: 'OpenAI'
apiKey: '${OPENAI_API_KEY}'
baseURL: 'http://librechat-mnemonic:8710/openai/v1'
models:
default: ['gpt-4o']
headers:
x-librechat-user-id: '{{LIBRECHAT_USER_ID}}'
x-librechat-conversation-id: '{{LIBRECHAT_BODY_CONVERSATIONID}}'
Restart LibreChat. Send a message. Type /memory status to confirm it is wired up.
The full example, including Anthropic and the MCP server, is in examples/librechat.yaml.
In-chat commands
The proxy answers these itself. The model is never called and no tokens are spent.
| Command | Effect |
|---|---|
/memory |
List the commands |
/memory on / /memory off |
Enable or disable memory for this chat |
/memory status |
Show the current setting, its source, and the project |
/memory default on|off |
Set your personal default for new chats |
/memory reset |
Drop this chat's override and follow your default |
/memory save <text> |
Store a memory now |
/memory search <query> |
Search memory without involving the model |
/memory forget <id> |
Delete a memory by id |
Precedence is per-chat, then per-user, then MEMORY_DEFAULT_ENABLED.
How project scoping works
mnemonic derives project identity from a working directory. Its detection order is the git remote of the enclosing repo, then the git root folder name, then the plain basename of the directory. This uses the third branch: each LibreChat project gets a directory under MNEMONIC_PROJECT_ROOT, and its name becomes the mnemonic project.
A LibreChat project called Home Network becomes /projects/Home Network, which mnemonic resolves to { id: "home-network", name: "Home Network", source: "folder" }.
Writes use scope: global with that directory as cwd. mnemonic stores the note in the main vault while stamping it with the detected project. The note's frontmatter carries project: home-network and projectName: Home Network. That is what "one global vault, partitioned by project" means in practice.
What each recall scope actually returns
Verified against mnemonic 0.42, because the tool descriptions are misleading on this point:
MNEMONIC_RECALL_SCOPE |
A chat in project "Home Network" sees |
|---|---|
project |
Only notes stamped home-network. Hard isolation. |
all (default) |
Everything in the vault, with home-network notes boosted. |
global |
Everything in the main vault, unboosted. |
Note that global does not mean "notes with no project". mnemonic's tool description still says it returns only unscoped memories; the implementation returns every note in the main vault regardless of project stamp. If you need memories from one project kept out of another, use project.
Three more things to know:
- The project directory must exist, and must exist on the filesystem of whichever process runs mnemonic. mnemonic calls
simpleGit(cwd)outside its error guard, so a missing path fails the whole call. In the default spawn mode this is handled for you. WithMNEMONIC_MODE=remoteit is your job. MNEMONIC_PROJECT_ROOTmust not be inside a git repository. If it is, mnemonic will attribute every memory to that repo instead of to the project.- Project names collide. Two LibreChat users with a project of the same name share one mnemonic project. This service is designed for single-user and small-trusted-team installs; see Limitations.
Configuration
Everything is environment driven. Only LIBRECHAT_MONGO_URI and UPSTREAMS have no useful default.
LibreChat
| Variable | Default | Description |
|---|---|---|
LIBRECHAT_MONGO_URI |
required | Connection string for LibreChat's MongoDB |
LIBRECHAT_MONGO_DB |
from the URI | Override the database name |
LIBRECHAT_USER_HEADER |
x-librechat-user-id |
Header carrying {{LIBRECHAT_USER_ID}} |
LIBRECHAT_CONVERSATION_HEADER |
x-librechat-conversation-id |
Header carrying {{LIBRECHAT_BODY_CONVERSATIONID}} |
Upstreams
UPSTREAMS is a JSON array. Each entry mounts a provider at /<name>/..., and everything after the name is forwarded verbatim.
| Field | Required | Description |
|---|---|---|
name |
yes | Path segment, e.g. openai → /openai/v1/chat/completions |
baseUrl |
yes | Provider root, such that <baseUrl>/v1/chat/completions is valid |
api |
no | openai (default) or anthropic |
apiKey |
no | Static credential replacing whatever LibreChat sends |
mnemonic
| Variable | Default | Description |
|---|---|---|
MNEMONIC_MODE |
spawn |
spawn runs the bundled mnemonic over stdio; remote connects to a streamable-http instance |
MNEMONIC_COMMAND |
bundled | Executable used in spawn mode |
MNEMONIC_URL |
none | Required when MNEMONIC_MODE=remote |
MNEMONIC_HEADERS |
{} |
JSON headers for the remote instance, e.g. auth |
MNEMONIC_VAULT_PATH |
/vault |
Vault directory, passed through as VAULT_PATH |
MNEMONIC_PROJECT_ROOT |
/projects |
Where per-project directories live |
MNEMONIC_WRITE_SCOPE |
global |
global stores in the main vault stamped with the project; project writes a project vault |
MNEMONIC_RECALL_SCOPE |
all |
project isolates, all boosts the current project, global returns the whole main vault. See the table above. |
MNEMONIC_RECALL_LIMIT |
6 |
Memories retrieved per turn |
MNEMONIC_MIN_SIMILARITY |
0.3 |
Similarity floor passed to recall |
MNEMONIC_TIMEOUT_MS |
20000 |
Per-call timeout |
MNEMONIC_TAG |
librechat |
Tag added to everything this service writes |
mnemonic's own variables (EMBED_PROVIDER, OLLAMA_URL, EMBED_MODEL, OPENAI_API_KEY, GEMINI_API_KEY, DISABLE_GIT, …) are passed through to the spawned process. See mnemonic's configuration.
Behaviour
| Variable | Default | Description |
|---|---|---|
MEMORY_DEFAULT_ENABLED |
true |
Whether memory is on for chats with no explicit setting |
MEMORY_RECALL_ENABLED |
true |
Set false to write memories without injecting them |
MEMORY_WRITE_MODE |
llm |
llm extracts automatically, explicit only on "remember that …", off disables writing |
MEMORY_MAX_CONTEXT_CHARS |
4000 |
Budget for the injected block |
MEMORY_QUERY_MESSAGE_COUNT |
3 |
User turns used to build the recall query |
MEMORY_MAX_PER_TURN |
3 |
Cap on memories written per exchange |
MEMORY_DEDUPE_THRESHOLD |
0.82 |
Recall score above which a candidate is treated as already known |
MEMORY_COMMAND_PREFIX |
/memory |
Change if it clashes with something |
MEMORY_PROJECTLESS |
global |
off disables memory entirely in chats not assigned to a project |
Extraction model
Leave unset to reuse the chat's own model and credentials. Setting a small dedicated model is cheaper.
| Variable | Default | Description |
|---|---|---|
EXTRACT_BASE_URL |
none | OpenAI-compatible base URL, including /v1 |
EXTRACT_MODEL |
none | Model name |
EXTRACT_API_KEY |
none | Bearer token |
EXTRACT_TIMEOUT_MS |
30000 |
Extraction is detached; a timeout drops the write, never the reply |
Service
| Variable | Default | Description |
|---|---|---|
PORT |
8710 |
Listen port |
HOST |
0.0.0.0 |
Listen address |
LOG_LEVEL |
info |
pino level |
MCP_ENABLED |
true |
Serve the MCP endpoint |
MCP_PATH |
/mcp |
Where to serve it |
MCP tools
Available at /mcp for LibreChat agents.
| Tool | Purpose |
|---|---|
search_memory |
Semantic search, project-scoped |
save_memory |
Store a note deliberately |
update_memory |
Correct an existing note |
forget_memory |
Delete a note |
memory_status |
Report the setting and project for this chat |
set_memory_enabled |
Toggle automatic memory for this conversation |
The server ships serverInstructions telling the agent that recall is already automatic, so it should reach for these only when the automatic path falls short.
Limitations
Worth knowing before you rely on it.
- The first turn of a brand new chat may miss its project. The conversation document may not be written when the first request arrives. The proxy retries once, and the post-turn write re-resolves the project, so writes are correct from turn one. The very first recall can fall back to global.
- Only traffic routed through the proxy is augmented. Endpoints configured to talk to a provider directly get no memory. That is deliberate: the proxy cannot see what it does not carry.
- Project names are the identity. Renaming a LibreChat project starts a new mnemonic project; the old memories stay under the old name. Directories under
MNEMONIC_PROJECT_ROOTcan be renamed to match, but nothing does it for you. - Multi-user installs share memory by project name. There is no per-user partition in the vault. Fine for a personal or small-team instance, wrong for a multi-tenant one.
- Automatic extraction is a judgement call made by a model. It will sometimes store something you would not have, and miss something you would.
MEMORY_WRITE_MODE=explicittrades recall for precision. - Tool-calling turns are passed through untouched. Memory is injected on the request and extracted from the final text, so intermediate tool rounds are not analysed separately.
Images and releases
Published to the GitHub Container Registry:
ghcr.io/claudedowling/librechat-mnemonic:latest # newest release
ghcr.io/claudedowling/librechat-mnemonic:0.1 # newest 0.1.x
ghcr.io/claudedowling/librechat-mnemonic:0.1.0 # exact version
ghcr.io/claudedowling/librechat-mnemonic:main # tip of main, unreleased
Built for linux/amd64 and linux/arm64, with SBOM and signed build provenance. Verify a pull with:
gh attestation verify oci://ghcr.io/claudedowling/librechat-mnemonic:latest \
--repo claudedowling/librechat-mnemonic
Pin to a minor tag such as :0.1 in production. latest moves across breaking changes while the project is pre-1.0.
To cut a release, bump version in package.json, then tag:
git tag v0.1.0 && git push origin v0.1.0
Development
npm install
npm test # unit tests
npm run typecheck
npm run dev # watch mode
Requires Node 22 or later.
The pieces worth understanding first: src/memory/service.ts holds the scoping rules that both entrypoints share, src/proxy/handler.ts is the request path, and src/mnemonic/projects.ts explains the directory trick and the constraints that come with it.
Licence
MIT
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