Context7
Up-to-date docs for AI agents
作者による説明(英語の原文)
Evidence-grounded agent memory with mandatory provenance, on local SQLite or Cloudflare D1
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
TITEN_MCP_URL, TITEN_API_KEY「秘密」と表示された値は、あなたのアカウントの鍵です。絶対に人に教えたり、チャットに貼り付けたりしないでください。
必要なもの
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
Claude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます
{
"mcpServers": {
"titen-memory": {
"command": "npx",
"args": [
"-y",
"titen-memory",
"mcp"
],
"env": {
"TITEN_MCP_URL": "your-value",
"TITEN_API_KEY": "your-value"
}
}
}
}ターミナルでこれを実行します
claude mcp add titen-memory --env TITEN_MCP_URL=your-value --env TITEN_API_KEY=your-value -- npx -y titen-memory mcp動かす前に、空欄の値を入力してください。
プロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"titen-memory": {
"command": "npx",
"args": [
"-y",
"titen-memory",
"mcp"
],
"env": {
"TITEN_MCP_URL": "your-value",
"TITEN_API_KEY": "your-value"
}
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"titen-memory": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"titen-memory",
"mcp"
],
"env": {
"TITEN_MCP_URL": "your-value",
"TITEN_API_KEY": "your-value"
}
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
これはパソコンで動くサーバーですが、ChatGPTがつなげるのはインターネット上のサーバーだけです。ほかのアプリを選んでください。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
TITEN_MCP_URL envこの設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
パソコンで動くサーバーです。インストールすると、ツール一覧がAIアプリに表示されます。
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月7日にチェック
レジストリ名は、リポジトリを所有するGitHubアカウント RamaAditya49 で確認済みです
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
これはパソコンで動くため、インターネット上のエンドポイントはありません
パソコンで動き、代わりにローカルの設定を使います
パソコンで動くサーバーです。ツール一覧を読み取れるのは、インターネット上のエンドポイントがある場合だけです
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
入力が必要なもの:TITEN_API_KEY
あなたのパソコンで動きます。必要なときにAIアプリが起動し、データは作者のサーバーを通りません(サーバー自体がオンラインサービスを呼び出す場合を除きます)。
GitHubリポジトリの最終更新は–、最新バージョン(0.7.2)がレジストリに届いたのは3 か月前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。パソコンにNode.jsも必要です。
同じカテゴリには:Context7, Codebase Memory, Exa
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i
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.
作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
Titen
Agent memory that runs with no API key, no LLM, and no embedding provider.
Every memory keeps its source, who may read it, and the evidence that contradicts it.
Website · Documentation · npm · Changelog
Built with C.A.D.I.S Agent .
If Titen is useful to you, a ⭐ on GitHub helps other people find it.
No account, no key, no configuration — but the CLI runs on [Bun](https://bun.sh/) 1.2 or newer, and refuses to start without it:
curl -fsSL https://bun.sh/install | bash # skip if you already have Bun
npx titen-memory mcp
With no environment set, that opens or creates ~/.titen/memory.db, writes a real organization, workspace, project and owner into it, and serves MCP over stdio in-process — no HTTP hop, no key to paste, and no outbound network call. Retrieval is FTS5, so nothing needs an embedding provider or a model.
curl -fsSL https://titen.dev/install.sh | bash does the same in one step: it adds Bun when it is missing, then installs the titen command.
Point an agent at it:
claude mcp add --transport stdio --scope user titen -- npx -y titen-memory mcp
Already using @modelcontextprotocol/server-memory? Titen serves the same nine tool names with the same schemas, and answers memory://knowledge-graph too, so a client does not notice the swap. On the first local-mode start it imports your existing graph. Pass the old store's path, because that server writes beside its own install rather than in the directory you launch it from:
claude mcp add --transport stdio --scope user titen \
--env MEMORY_FILE_PATH=/path/to/memory.jsonl -- npx -y titen-memory mcp
Without it Titen still checks the working directory, its node_modules, and npm's npx cache — and says on stderr when it found nothing, rather than starting empty in silence. Point titen at a served instance later by setting TITEN_MCP_URL and TITEN_API_KEY — full setup below.
Audit what any agent memory store has accumulated, including one Titen does not own:
npx titen-memory audit ./memory.json
package.json declares none. What it needs is Bun and one SQLite file; everything else is the standard library and Web APIs.titen_* plus the nine reference-server names — with search_nodes routed through real retrieval rather than a substring scan, and your existing memory.json imported on first run.titen audit reads a reference-server memory.json, a Mem0 export, or a Titen store, and reports duplicates, recall loops, secret patterns and staleness with per-item evidence you can check by hand.@modelcontextprotocol/server-memory?That server had 106,662 downloads in the week of 31 July 2026 — it is the default memory for a large part of the MCP ecosystem, and it is deliberately minimal. Reading its published 2026.7.4 tarball: the store is one newline-delimited JSON file rewritten in full on every mutation, and a search is
graph.entities.filter(e => e.name.toLowerCase().includes(query.toLowerCase()) || ...)
String.includes on a lowercased needle. No tokenizer, no stemming, no ranking — results arrive in insertion order — no scoping or authorization, and no eviction, so the file grows without bound and every call is O(n) in the whole graph. Ask it *"which service handles refunds"* and it matches nothing unless that exact sentence is stored.
Titen answers the same nine tool names, with the same argument schemas, and the same memory://knowledge-graph resource, so a client does not notice the swap. What changes is underneath: search_nodes runs the real retrieval path — FTS5 with stemming, ranked best-first, and the vector index when one is configured — and every read is scoped to a subject and filtered by authorization before it is retrieved, not after.
@modelcontextprotocol/server-memory | Titen | |
|---|---|---|
| Search | String.includes, insertion order | FTS5 + stemming, ranked, optional vectors |
| Scope | the whole graph, always | org / subject / project / workspace, enforced pre-retrieval |
| Contradictions | overwritten | kept, linked to evidence, flagged |
| Growth | full-file rewrite, unbounded | SQLite, retention and eviction policies |
| Provider | none | none — no key, no LLM, no embedding provider |
Import is on first start; the switch is above.
Every published memory benchmark measures retrieval on a corpus somebody curated. The failure people actually report is on the write side: a store fills with copies of its own output. The one public audit of a production store found 97.8% of 10,134 entries were junk after 32 days. Nothing measures that.
npx titen-memory audit ~/.titen/memory.db # a Titen store
npx titen-memory audit ./memory.jsonl # @modelcontextprotocol/server-memory npx titen-memory audit ./mem0-export.json --json # a Mem0 export
Five counts — exact duplicate, near duplicate, recall loop, secret pattern, stale — each with per-item evidence you can check by hand. No network, no model, no upload: it opens the path read-only and prints a report; sharing it is your decision. A store that lacks the signal a metric needs is reported as *not measurable from this export*, never as a failure. There is no composite score and there is no leaderboard.
The detection rules are published in audit rules. Titen's own numbers — including 17.9% duplicates and 96.7% stale in its own store, and a compatibility-surface defect the tool found in Titen itself — are in the self-report.
Titen's default memory model is caller-authored claims. consolidate() takes statements you wrote, each explicitly linked to a source observation you already recorded. Titen does not read a transcript and decide on its own what is worth remembering.
That is deliberate. Every claim has an author, a source, and a scope, which is what makes provenance, permission, conflict, and audit answerable at all. It is also a real cost, and it is the honest comparison point: systems that derive memory from raw dialogue do work Titen hands back to you.
Model-assisted derivation and reflection are implemented and ship in the package, but they are activation-gated and no candidate model has passed the gate — the best result on record is 65.56% against a 90% contract threshold. Treat them as unfinished work with a public gate, not as a feature you can simply switch on. The roadmap carries the current evidence.
| Question | Titen's answer |
|---|---|
| Where did this memory come from? | Every claim points back to source observations and keeps its version history. |
| May this agent see it? | Organization, subject, project, workspace, and visibility checks run before retrieval. |
| What if two sources disagree? | Contradictions remain visible until an explicit lifecycle action resolves them. |
| Who is doing the work? | Leases prevent silent double ownership; checkpoints and handoffs make work resumable. |
| Can we audit or move it? | Canonical records live in SQL, with authenticated audit trails and versioned JSONL export/import. |
| Do we need an LLM or vector database? | No. The default install is FTS-only with no provider at all; embeddings and model enrichment are opt-in projections. Whether the vector arm helps depends on the store shape — see below. |
Agents connect through authenticated REST, Streamable HTTP MCP, the titen mcp stdio bridge, or the TypeScript SDK. Titen never treats retrieved memory as an instruction, and it does not run agent loops.
On LongMemEval-S (MIT, externally authored, 500 instances, 246,930 turns), our own scorer, failures kept in the denominator, protocol pre-registered before each run. Full table and method at titen.dev/benchmark.
Every figure below names its condition, because the condition moves recall@1 by 63 points on the same corpus. *Per-instance (scoped)* gives each question its own ~50-session haystack — the single-subject shape
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