io.github.DioNanos/mcp-memory-rs
FreeNot checkedLocal-first agent memory: versioned JSON categories, BM25 search, per-device ACL, fleet sync.
About
Local-first agent memory: versioned JSON categories, BM25 search, per-device ACL, fleet sync.
README
CI Tests License: Apache-2.0 Rust Local First
Local-first MCP memory server in pure Rust. Persistent, versioned, queryable memory for AI agents — owned by the user, not by a platform.
State lives on your disk as plain JSON categories backed by SQLite (FTS5). Every write is versioned and backed up. A fleet of devices syncs through an optional HTTP endpoint with merkle manifests and optimistic concurrency. No cloud account, no embedding service, no network dependency in the default mode.
Why
Agent memory tied to a vendor dies with the vendor session. This server keeps the agent's long-lived state — identity, projects, infrastructure notes, per-device workflows — in files you can read, grep, diff, and back up yourself. Any MCP client (Claude Code, Codex, or anything speaking MCP stdio) gets the same memory; swapping the model does not lose the state.
Design choices that follow from that:
- Local-first: the stdio server works fully offline against local storage. Sync is a separate, explicit step — never a hidden dependency.
- Plain storage: one JSON file per category plus a SQLite index. The database can be rebuilt from the files; the files are the truth.
- Versioning by default: every write keeps history; deletes create a
backup first.
memory_historyandmemory_compactmanage the tail. - Concurrency-safe writes:
expected_hashturns clobbering races between concurrent agents into explicit conflicts. - Zero ML in the core: full-text search is SQLite FTS5 with BM25;
memory_search_semanticadds an optional TF-IDF hybrid. No model downloads.
The pair: for corpus recall (chunked documents, BM25 retrieval, original-text injection) see the companion server mcp-vl-msa-rs. This server holds the curated agent state; that one holds the queryable corpus.
flowchart LR
A["AI agent<br/>(any MCP client)"]
A -->|"curated state<br/>read / write / sync"| M["mcp-memory-rs<br/><i>the notebook</i>"]
A -->|"corpus recall<br/>index / search / fetch"| V["mcp-vl-msa-rs<br/><i>the library</i>"]
M --- D1[("JSON categories<br/>SQLite FTS5")]
V --- D2[("tantivy BM25<br/>collections")]
Install
Prebuilt binary (recommended) — download the archive for your platform from the latest release, extract, and point your MCP client at the binary:
tar xzf mcp-memory-rs-x86_64-unknown-linux-gnu.tar.gz
install -m755 mcp-memory-rs-*/mcp-memory-rs ~/.local/bin/
Prebuilt targets (Linux + Android): x86_64-unknown-linux-gnu,
x86_64-unknown-linux-musl, aarch64-unknown-linux-gnu,
aarch64-unknown-linux-musl (edge / ARM / Termux), aarch64-linux-android.
macOS: no prebuilt binary is shipped (it would need Apple code-signing).
Install from source instead — cargo install compiles it on your Mac in one
command, no signing needed:
cargo install --git https://github.com/DioNanos/mcp-memory-rs --locked
--locked uses the committed Cargo.lock (reproducible build).
Quick start
cargo build --release
# stdio MCP server, offline mode (default)
./target/release/mcp-memory-rs
Claude Code (~/.claude.json) or any MCP client:
{
"mcpServers": {
"memory": {
"command": "/path/to/mcp-memory-rs",
"env": {
"MCP_MEMORY_CONFIG": "/home/me/.config/mcp-memory-rs/config.toml",
"MCP_MEMORY_REQUIRE_CONFIG": "1",
"MCP_MEMORY_MODE": "offline",
"MCP_DEVICE": "my-laptop"
}
}
}
}
Codex (~/.codex/config.toml):
[mcp_servers.memory]
command = "/path/to/mcp-memory-rs"
env = { MCP_MEMORY_CONFIG = "/home/me/.config/mcp-memory-rs/config.toml", MCP_MEMORY_REQUIRE_CONFIG = "1", MCP_MEMORY_MODE = "offline", MCP_DEVICE = "my-laptop" }
# auto-approve read-only tools (memory_read/list/search/…); writes still gated
default_tools_approval_mode = "approve"
Configuration is TOML — copy config/example.toml to
~/.config/mcp-memory-rs/config.toml and adjust it. The server auto-discovers
that XDG-style path. Environment variables override file values (MCP_DEVICE,
MCP_MEMORY_MODE, MCP_MEMORY_DIR, …); managed deployments should set
MCP_MEMORY_REQUIRE_CONFIG=1 so a missing config fails closed.
Memory model
Memory is organized in categories: named JSON documents (base,
projects, my-laptop, workflow_my-laptop, …). Reads return the document
plus metadata (content hash, size, last writer, timestamp). Writes replace the
category or, with merge=true, patch it per top-level key.
Access control
Multi-device fleets get a small, explicit ACL ([acl] in the config):
| Rule | Effect |
|---|---|
admin_devices |
Listed devices write everything. |
device_categories |
Device name writes category name and workflow_name — its own namespace only. |
| agent scope | Device foo-agent writes foo_* categories. |
| everyone | All devices read everything. |
Unknown categories are denied for non-admin writers — fail closed.
Fleet sync
Each node runs local-first; one node (or any number) exposes the HTTP API as a
sync remote. sync_manifest builds a merkle-rooted fingerprint of all
categories; sync_diff compares manifests; memory_sync pushes dirty
categories or pulls remote changes. Conflicts between nodes are resolved by
the configured conflict_strategy (last-write-wins by default);
expected_hash preconditions protect direct writes (MCP and HTTP), not the
sync envelope.
The HTTP API is an admin/sync plane: the bearer token grants full access to every category. Per-category ACL applies on the MCP stdio surface, where the device identity is known locally; HTTP callers are identified only by the shared token, so no per-device ACL is enforced there.
The HTTP server requires MCP_MEMORY_TOKEN and refuses to start without
it. Bind it to loopback (the default) and tunnel between nodes; do not expose
it to the public internet.
MCP_MEMORY_TOKEN=<secret> ./target/release/mcp-memory-rs --http
Tool surface
| Tool | Description |
|---|---|
memory_read |
Read a category (optional field filtering). |
memory_write |
Replace or merge-patch a category; versioned; expected_hash precondition. |
memory_append |
Append a timestamped entry to a bounded append-only log category; auto-prunes by max_entries/max_age_days. For event streams / session journals, so they don't bloat memory categories. |
memory_delete |
Delete a category (backup created first). |
memory_list |
All categories with hash/size/last-update metadata. |
memory_search |
FTS5 full-text search, BM25 ranking, category/date/actor filters, snippets. |
memory_search_semantic |
Hybrid TF-IDF + FTS5 search. |
memory_history |
Version history of a category. |
memory_delta |
Changes since a known hash (cheap polling). |
memory_context |
Multi-category warmup read, token-budget oriented. |
memory_compact |
Prune old versions and backups. |
memory_status |
Local-first status: dirty queue, manifest hash, last sync. |
memory_doctor |
Diagnostics: paths, database, categories, sync config. |
sync_manifest |
Merkle-rooted manifest of all categories. |
sync_diff |
Compare local vs remote manifest: push/pull/conflict sets. |
sync_push / sync_pull |
Export/import sync envelopes. |
memory_sync |
One sync step against the configured remote (push_dirty / pull_remote). |
The same surface is available over HTTP (/api/v1/*) for non-MCP consumers;
/health is unauthenticated, everything else requires the bearer token.
AI client compatibility
The server is built to be self-explanatory to a weak client model:
- At
initializeit returns an instructions string describing the memory model and the entry-point tools. Some lightweight clients ignore this field; if your client never surfaces it, read the tool descriptions instead — they carry the same guidance (e.g.memory_readtakescategory, notkey). - Read-only tools are annotated
readOnlyHint, so a client such as Codex can auto-approve them. On Codex, anunsupported call/user cancelledresult usually means the tool-approval gate fired, not a server fault — setdefault_tools_approval_mode = "approve"(see the Codex snippet above). - The server speaks the standard MCP handshake. A client must complete
initializeand sendnotifications/initializedlike any MCP client.
Storage layout
With no config and strict mode disabled, standalone base_dir remains
~/.memory for compatibility. The auto-discovered example config uses
~/.local/state/mcp-memory-rs (XDG-style). Config resolution is: explicit
MCP_MEMORY_CONFIG, $XDG_CONFIG_HOME, $HOME/.config, legacy cwd-local
memory-config.toml, then standalone defaults. Either way the layout is:
<base_dir>/
├── categories/ # one .json file per category — the source of truth
├── backups/ # automatic pre-delete/pre-overwrite backups
└── memory.db # SQLite: FTS5 index, versions, sync state (rebuildable)
Building and testing
cargo build --release # single static-friendly binary
cargo test # unit + integration tests
cargo clippy --all-targets -- -D warnings
No build-time network access, no C dependencies beyond bundled SQLite.
License
Apache-2.0. See LICENSE.
Installing io.github.DioNanos/mcp-memory-rs
This server has no published package — it is built from source. Open the repository and follow its README.
▸ github.com/dionanos/mcp-memory-rsFAQ
Is io.github.DioNanos/mcp-memory-rs MCP free?
Yes, io.github.DioNanos/mcp-memory-rs MCP is free — one-click install via Unyly at no cost.
Does io.github.DioNanos/mcp-memory-rs need an API key?
No, io.github.DioNanos/mcp-memory-rs runs without API keys or environment variables.
Is io.github.DioNanos/mcp-memory-rs hosted or self-hosted?
Self-hosted: the server runs locally on your machine via the install command above.
How do I install io.github.DioNanos/mcp-memory-rs in Claude Desktop, Claude Code or Cursor?
Open io.github.DioNanos/mcp-memory-rs on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.
Related MCPs
GitHub
PRs, issues, code search, CI status
by GitHubFilesystem
Secure file operations with configurable access controls.
Memory
Knowledge graph-based persistent memory system.
Template MCP Server
A CLI tool to create a new Model Context Protocol server project with TypeScript support, dual transport options, and an extensible structure
by mcpdotdirectCompare io.github.DioNanos/mcp-memory-rs with
Not sure what to pick?
Find your stack in 60 seconds
Author?
Embed badge for your README
Browse similar
All development MCPs
