Context7
Up-to-date docs for AI agents
作者による説明(英語の原文)
Session memory for coding agents: local-first recall, drift detection, on-device inference.
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。
BRAVE_API_KEY, GEMINI_API_KEY, SUPABASE_URL, SUPABASE_KEY, PRISM_USER_ID, GCP_PROJECT_ID, VERTEX_LOCATION, VERTEX_DATA_STORE_ID「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": {
"prism-coder": {
"command": "npx",
"args": [
"-y",
"prism-mcp-server"
],
"env": {
"BRAVE_API_KEY": "your-value",
"GEMINI_API_KEY": "your-value",
"SUPABASE_URL": "your-value",
"SUPABASE_KEY": "your-value",
"PRISM_USER_ID": "your-value",
"GCP_PROJECT_ID": "your-value",
"VERTEX_LOCATION": "your-value",
"VERTEX_DATA_STORE_ID": "your-value"
}
}
}
}ターミナルでこれを実行します
claude mcp add prism-coder --env BRAVE_API_KEY=your-value --env GEMINI_API_KEY=your-value --env SUPABASE_URL=your-value --env SUPABASE_KEY=your-value --env PRISM_USER_ID=your-value --env GCP_PROJECT_ID=your-value --env VERTEX_LOCATION=your-value --env VERTEX_DATA_STORE_ID=your-value -- npx -y prism-mcp-server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": {
"prism-coder": {
"command": "npx",
"args": [
"-y",
"prism-mcp-server"
],
"env": {
"BRAVE_API_KEY": "your-value",
"GEMINI_API_KEY": "your-value",
"SUPABASE_URL": "your-value",
"SUPABASE_KEY": "your-value",
"PRISM_USER_ID": "your-value",
"GCP_PROJECT_ID": "your-value",
"VERTEX_LOCATION": "your-value",
"VERTEX_DATA_STORE_ID": "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": {
"prism-coder": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"prism-mcp-server"
],
"env": {
"BRAVE_API_KEY": "your-value",
"GEMINI_API_KEY": "your-value",
"SUPABASE_URL": "your-value",
"SUPABASE_KEY": "your-value",
"PRISM_USER_ID": "your-value",
"GCP_PROJECT_ID": "your-value",
"VERTEX_LOCATION": "your-value",
"VERTEX_DATA_STORE_ID": "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。
SUPABASE_URL envPRISM_USER_ID envGCP_PROJECT_ID envVERTEX_LOCATION envVERTEX_DATA_STORE_ID 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6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 dcostenco 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:BRAVE_API_KEY, GEMINI_API_KEY, SUPABASE_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(20.22.4)がレジストリに届いたのは14 日前です。
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。
Give your AI agent memory that lasts — and see the cloud tokens it never had to spend. Persistent sessions, knowledge graphs, offline tool-routing, and an auditable savings meter. Fully local and free.
Current release: v20.22.5 — local oMLX images and memory accounting
Choose an independent image model from discovered local inventory. Compatible
oMLX servers support controlled PNG image requests with local screening and
generation. Image accuracy depends on the model; Ollama image execution remains
unavailable for the saved image choice. See the oMLX guide.
*Local AI dashboard development preview. Screenshots below use an isolated demo with illustrative inventory and responses; they do not show a live account or prove model accuracy. The npm release may show an earlier interface.*
Prism Coder is an MCP server that gives Claude, Cursor, and other AI tools long-term memory that survives across sessions. It ships with the open-weight prism-coder model fleet (2B–27B) for fast, offline tool-routing — no cloud required. And it keeps score: every call served locally is metered, so prism savings shows the token volume that never reached your cloud model — measured honestly, in tokens.
No account needed. No API keys. Runs on your machine. A paid subscription adds cloud sync, higher model tiers, and team features through the Synalux portal.
prism savings (or the local_savings tool from any host) reports the token volume local serving kept off your cloud model: headline, local share, per-model breakdown. It reports tokens, never an invented dollar figure, and prints its assumptions and known undercounts inline — a number you can check, not marketing.route_guard: "local" disables that correction only. cloud_fallback: false forbids cloud inference fallback and verify: false (with no evidence) disables the grounding verifier. With all three off, no request carries your prompt, draft or evidence; the per-call entitlement check and telemetry still contact the portal and carry neither.prism connect configures Claude Code, Claude Desktop, Cursor, Gemini CLI, and Codex while preserving unrelated settings.prism connect adds two small ones on top: mid-session prompt routing, and a post-compaction re-injection of the protected-floor digest.PRISM_DARK_FACTORY_ENABLED=false disables Factory after an MCP restart. Try the three-test filename fix.Run prism dashboard, open Account & Settings → Local AI, then work through Connection → Models → Test. These controls configure local inference; session memory continues to work without installing a model.
| Step | What you do | What to expect |
|---|---|---|
| 1. Connection | Choose an existing oMLX server or a Prism-managed installation, then Preview connection. | Review the effect on coder, reviewer and image assignments before Use this server switches the shared oMLX connection. Saved model IDs are preserved. |
| 2. Models | Choose coder and reviewer models for each backend and Save coding preference. Save the separate Image model form independently. | Saving records a choice; it does not download or load weights. Missing saved IDs stay visible instead of being silently replaced. |
| 3. Test | Select backend and purpose, then Test saved model. | A small request may load the saved model. The result reports execution or a blocking reason, with no cloud inference fallback. |
Coding and review. Auto prefers configured oMLX for eligible coding. You can choose Ollama instead; explicit task choices take precedence. oMLX coding and review need the integration's separate text safety classifier. Local drafts and reviews still need host inspection and tests.
Images have their own choice. Select an oMLX vision model under Image model, then Save image preference. It may be the same model used for coding, but the setting is independent. Refresh image models reads metadata without loading a model. Vision metadata and RAM estimates are advisory; each request repeats compatibility and resource checks. The saved Ollama image option currently refuses execution; leave the image backend Not selected to retain existing image routing.
Read image-test results in two parts. The built-in diagnostic sends a red square. Reference facts describe that known PNG; AI observations contain the model's answer. A wrong answer cannot change the reference. A passing test proves execution, not visual accuracy. User images do not receive catalog facts from this diagnostic. Starting another test or changing backend or purpose clears the previous image result.
Server setup is optional and separate from npm. On supported Apple Silicon Macs, expand Install or update a Prism-managed server to install the server without downloading the optional coding starter pack. Add models through Open oMLX model manager. Installing a server update does not restart it or switch your connection. Restart managed server interrupts local inference and is available only when Prism can establish managed ownership and idle activity. External servers use their own upgrade and restart procedure.
Updating the Prism npm package or restarting your AI client does not upgrade an external oMLX server. If image status says Server update required, follow the existing-server upgrade guide. Tested Prism-compatible source identifies the compatible revision; Latest upstream releases is for release notes and may lack Prism's routes. See the oMLX guide for requirements and troubleshooting.
Memory search automatically applies ACT-R ranking: relevance plus recency, frequency and memory associations. No upvote or prompt instruction is required. To opt out, use Account & Settings → Preferences → Automatic Memory Ranking (ACT-R), then restart your AI client. PRISM_ACTR_ENABLED=false also disables it. This ranking is separate from the neural graph's stored importance filter.
npm install -g prism-mcp-server
prism connect prism dashboard
Use prism connect --dry-run to preview changes, prism connect --all to configure every detected host, or prism connect --refresh to reconcile Prism-managed entries after an upgrade. Restart the host after connecting.
prism dashboard opens the current local Mind Palace without a Synalux login. Prism works locally without an account, API key, or cloud subscription. Add a Synalux subscription when you want cloud memory, paid-tier skills, or team features.
To check your plan, open ⚙ Account & Settings → Account in the dashboard. Free users see Start 14-day trial; paid users see Manage subscription. During a trial, the same panel shows the paid tier and exact end date. No card is required to start. Add payment details before the end date to continue; if you do not, the subscription cancels and local Prism Free remains available. You can also compare plans directly at synalux.ai/pricing#prism-plans.
After a few sessions, ask what it's been worth:
prism savings --period month
💾 Local serving — LAST 30 DAYS
~510K tokens kept off your cloud model 53 call(s) served locally of 58 routed (91%)
Your numbers will differ — that's the point: it reports what *your* machine actually served, not a projection. Full report anatomy and the honesty rules behind it are in the local_savings section.
Prism also ships as a plugin, which registers the MCP server and the startup skill for you.
Both hosts install straight from this repository. There is nothing to host and no server to run: the catalogue is the .claude-plugin/marketplace.json file committed here, and your client clones it from GitHub.
Claude Code:
claude plugin marketplace add dcostenco/prism-coder
claude plugin install prism-coder@prism
Codex:
codex plugin marketplace add dcostenco/prism-coder
codex plugin add prism-coder@prism
The plugin registers prism-mcp via npx -y prism-mcp-server. If you already configured Prism by hand — prism connect writes an mcp_servers.prism-mcp entry — you have that server twice under one key. Install the plugin or run prism connect, not both.
prism connect changes about host subagentsconnect steers bounded work to prism_infer on your machine rather than to host-spawned agents. What it writes differs per host, and it does not disable subagents everywhere — Claude Code keeps them and is pointed at an economy model instead. Prism's local workers stay available over MCP in every case.
| Host | Setting written | Effect |
|---|---|---|
| Claude Code | env.CLAUDE_CODE_SUBAGENT_MODEL = "sonnet" in ~/.claude/settings.json | Subagents stay enabled, pinned to an economy model. Fan-out is discouraged by policy text, not by config |
| Gemin
冒頭だけを表示しています。続きはリポジトリで読めます