Context7
Up-to-date docs for AI agents
Beschreibung vom Entwickler (englisches Original)
Local-first agent memory: versioned JSON categories, BM25 search, per-device ACL, fleet sync.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Der Entwickler hat in der Registry keine Installationsangaben gemacht. Sieh dir unten die README des Entwicklers an.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 8. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto DioNanos bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.2.1) kam vor 5 Monaten in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code.
In derselben Kategorie: Context7, Codebase Memory, Exa
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
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.
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:
memory_history and memory_compact manage the tail.expected_hash turns clobbering races between concurrent agents into explicit conflicts.memory_search_semantic adds 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 (any MCP client)"] A -->|"curated state read / write / sync"| M["mcp-memory-rs the notebook "] A -->|"corpus recall index / search / fetch"| V["mcp-vl-msa-rs the library "] M --- D1[("JSON categories SQLite FTS5")] V --- D2[("tantivy BM25 collections")]
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).
cargo build --release
./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" }
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 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.
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.
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 | 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.
The server is built to be self-explanatory to a weak client model:
initialize it 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_read takes category, not key).readOnlyHint, so a client such as Codex can auto-approve them. On Codex, an unsupported call / user cancelled result usually means the tool-approval gate fired, not a server fault — set default_tools_approval_mode = "approve" (see the Codex snippet above).initialize and send notifications/initialized like any MCP client.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) └── memory.db-wal # write-ahead log (WAL mode; do not copy or delete by hand)
Every writer — one stdio server per client plus the optional --http instance — opens its own SQLite connection on the same file. Since 0.3.2 each mutation runs inside a BEGIN IMMEDIATE transaction: SQLite is the mutex that serializes writers *across processes*, so an append (read → modify → write) can never lose another process's entry. Lock acquisition is retried with jittered backoff inside one total budget; when it expires the call fails with a clear Store busy … retry later error instead of hanging or corrupting anything.
[storage]
journal_mode = "wal" # "wal" (default) or "delete" synchronous = "full" # "full" (default, durable) or "normal" sqlite_busy_timeout_ms = 200 # per-statement SQLite busy handler lock_deadline_ms = 10000 # total wait for the write lock per mutation
Category JSON files are written crash-safely: the new content is staged next to the file (a name unique to the transaction), the SQLite rows are committed, then the staged file is renamed into place. A process that dies in between leaves a staged file whose fate is decided by its hash under the next write lock (matching the committed hash → promoted; otherwise → discarded). Readers never rename or delete anything: they serve whichever file carries the committed hash. memory_write merge=true, the log/memory kind check and the optional expected_hash compare-and-swap all run inside the same lock.
memory.db alone is not a backup (WAL, JSON files). Use the CLI:
mcp-memory-rs --snapshot /path/to/snap-2026-09-15 --with-backups # db + json + backups + manifest
mcp-memory-rs --restore /path/to/snap-2026-09-15 --stopped mcp-memory-rs --verify-store # read-only: db vs json, pending files
--verify-store never opens a Store (no PRAGMA, schema or reconcile): it is safe on a store another binary still owns. A store written by a version older than 0.3.2 can hold categor
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