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PopNx MCPAIを使う人のためのMCPサーバー · やさしい言葉で解説

sf-intelligence — Salesforce org intelligence for AI agents

作者:PranavNagrechaバージョン 0.3.3i★ –iパソコンで動く
レジストリ名io.github.PranavNagrecha/sf-intelligence

インストール

概要

作者による説明(英語の原文)

Offline, read-only MCP knowledge base for one Salesforce org's metadata, deps & impact.

PopNx MCPの3つの柱

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。

できること

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。

  • 接続方法: パソコンで動く
  • トランスポート: stdio
  • カテゴリ: マーケティング・SNS
  • 入力が必要なもの:SFI_VAULT

インストール

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。

インストールの前に

必要なもの

  • npmNode.jsのインストール(npxコマンドに必要)

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": {
    "sf-intelligence": {
      "command": "npx",
      "args": [
        "-y",
        "sf-intelligence"
      ],
      "env": {
        "SFI_VAULT": "your-value"
      }
    }
  }
}

ターミナルでこれを実行します

claude mcp add sf-intelligence --env SFI_VAULT=your-value -- npx -y sf-intelligence

動かす前に、空欄の値を入力してください。

Cursorで開く

または、設定を自分でコピーする

プロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます

{
  "mcpServers": {
    "sf-intelligence": {
      "command": "npx",
      "args": [
        "-y",
        "sf-intelligence"
      ],
      "env": {
        "SFI_VAULT": "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。

VS Codeで開く

または、設定を自分でコピーする

プロジェクトの .vscode/mcp.json に貼り付けます

{
  "servers": {
    "sf-intelligence": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "sf-intelligence"
      ],
      "env": {
        "SFI_VAULT": "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。

自分で入力する値

  • SFI_VAULT 必須 env
    Absolute path to the org-kb vault this server should answer from, e.g. /org-kb. Set this: without it the server falls back to ./org-kb relative to whatever directory your MCP host happens to launch i…

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。

できること

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。

基本チェックi

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

  • ✓ 合格

    作者とリポジトリが一致

    レジストリ名は、リポジトリを所有するGitHubアカウント PranavNagrecha で確認済みです

  • … 未チェック

    今もメンテナンスされている

    このリポジトリはまだGitHubから読み取っていません

  • … 未チェック

    ライセンスがある

    このリポジトリはまだGitHubから読み取っていません

  • – 対象外

    エンドポイントが応答する

    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

  • – 対象外

    OAuthでサインイン

    パソコンで動き、代わりにローカルの設定を使います

  • … 未チェック

    ツールの説明に隠れた指示がない

    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

マーケティング・SNSのほかのサーバーとの比較i

  • このカテゴリのほかの2985件のうち0%よりスターが多い
  • このカテゴリのほかの2985件のうち46%より最近レジストリに公開
  • 基本チェックの結果が、このカテゴリのほかの2985件のうち100%と同じかそれ以上

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。

よくある質問

sf-intelligence — Salesforce org intelligence for AI agentsは安全ですか?

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。

どんなキーやコードが必要ですか?

入力が必要なもの:SFI_VAULT

パソコンで動きますか、それともクラウドですか?

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)。

今もメンテナンスされていますか?

GitHubリポジトリの最終更新は–、最新バージョン(0.3.3)がレジストリに届いたのは34 日前です。

どのアプリで使えますか?

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。

代わりに使えるものは?

同じカテゴリには:MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer

代わりの候補

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

Google Analytics MCP

作者:surendranb

GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.

パソコンで動く★ 244MIT10 日前更新
インストール

作者のREADME

READMEを開く

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。

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sf-intelligence

Know what breaks before you change Salesforce. Ask the AI assistant you already use about your org. sf-intelligence runs on your computer, never writes to your org, and every answer names the components it came from.

Website, demo and docs: [sfi.auditforce.cloud](https://sfi.auditforce.cloud) · Works in Claude Code, Claude Desktop, Cursor, VS Code + Copilot and Codex.

What it answers

The questions below were checked by an outside reviewer against a real production org (about 4,700 components) by reading the raw metadata. The answers were right.

AskWhat you get back
Where is this field used?Every Apex class, flow, layout, validation rule, report and page that references it, each with how it was found (declared, parsed or heuristic)
Can I delete this field?A verdict (safe, risky, blocking, review) with the reasons and the components behind each one, plus what was *not* checked
What happens when I save a record?The save order for one object and one event: triggers, validation rules, flows, approvals, in the sequence they run
Which Apex is dead?Classes and triggers nothing calls, with the honest tier (definitely, likely, uncertain) and why
Who can see or edit this?Effective permissions from profile plus permission sets, and why a given user cannot see a record

A real answer from the built-in demo org (a solar installer called Verdant), unedited:

Can I delete `Project__c.Risk_Score__c`? Not safe to delete: blocking. ProjectTriggerHandler writes it and ProjectTriggerHandlerTest reads it (parsed from the Apex); the Residential page layout shows it (declared). Checked: Apex, flows, workflow rules, validation rules, layouts. Not checked: assignment, auto-response and escalation rules, because they were not retrieved.

Try it in three commands

npm install -g sf-intelligence

claude mcp add --scope user sf-intelligence-demo -- npx -y sf-intelligence demo # a built-in demo org, no Salesforce login; then ask your assistant a question cd your-sfdx-project && sfi init --target-org my-org-alias # then: connect your own org (read-only retrieve)

sfi demo on its own starts an MCP server and waits for a host; it is not a command to run in a terminal.

Then register the server in your AI host; the install guide has the exact block for each host. Or one click: Try the built-in demo org in Cursor in one click (no Salesforce login). AI agents installing this server: see llms-install.md.

By default your assistant sees 16 tools: the eight that answer the questions above and eight that help it find its way (sfi.resolve, sfi.search_components, sfi.get_component, sfi.health_check, sfi.list_analyses, sfi.describe_analysis, sfi.run_analysis, sfi.live_consent). Every other analysis sits behind one gateway tool, sfi.run_analysis, and is listed by sfi.list_analyses. The vault is a local folder, answers are served offline, and the optional live read-only plane is off until you turn it on. What your AI assistant does and does not see is in Privacy.

For engineers: how the vault, the dependency graph and your assistant fit together is in How it works; what is deliberately not modeled is in What it does NOT do.

Ask it like a person

You don't need to know the exact API name of anything. A typo-tolerant resolver turns messy phrasing into the right component, and when it isn't sure it asks you a clarifying question instead of guessing:

You: where's the emale field?

It: I found several matches for "email" — which did you mean?

· Email__c on Account

· Email__c on Contact

· Alternate_Email__c on Lead

You: what about the paymnet object?

It: Payment__c — one confident match.

You: is there a "warranty fee" field?

It: Nothing matched that confidently. Your vault was last refreshed on

2026-05-20 — want to pull fresh metadata from the org (/sfi-refresh) in case

it's new, or rephrase?

It never silently commits to a guess. When several components are plausible it asks which you meant; when nothing matches it offers to refresh from the org or stop. A high match score is string similarity, not proof.

How it works

One read-only refresh turns your org into a local vault: the raw metadata, one Markdown page per component, and a dependency graph. From then on every question is answered offline. Your AI assistant resolves the name you used, calls one of the 16 default tools (or sfi.run_analysis for any other analysis), and builds its answer only from what came back, citing each component.

flowchart TB

subgraph REFRESH["Refresh — once, and whenever the org changes"] direction LR ORG[("Salesforce org")] -->|"sf project retrieve (read-only)"| SRC["source/ raw metadata"] SRC -->|"extract + parse Apex / Flow / XML"| VAULT[("Local vault Markdown + DuckDB graph")] end

subgraph ASK["Ask — every question, offline on your machine"] direction TB Q["Your question (plain language)"] --> HOST["Your AI assistant (Claude, Cursor, Copilot, Codex)"] HOST -->|"1 · sfi.resolve"| RESOLVE["The component you meant (or a clarifying question)"] RESOLVE --> HOST HOST -->|"2 · a core tool, or sfi.run_analysis for the rest"| TOOLS["sfi.* analysis"] TOOLS -->|"read"| VAULT TOOLS -.->|"opt-in, read-only, capped"| LIVE[("Live org")] TOOLS -->|"cited components + confidence

  • what was not checked"| HOST HOST --> ANS["Grounded answer"] end

Every box on the Ask path runs on your machine; the dotted edge to the live org is the only one that can touch Salesforce, and only after you opt in.

How it stays honest

Every answer is built from tool output, never from general Salesforce knowledge. Each relationship carries how it was found: declared (stated in the metadata), parsed (from Apex, Flow or formula source) or heuristic (pattern matching, so spot-check before acting). Each answer says which metadata families were checked and which were not, so "nothing references this" always means "no evidence in what was retrieved". A request to change the org is refused and answered with the read-only check that fits instead. For "what does this imply" questions, a deterministic, offline concept model of general Salesforce truth (never your org's data) adds cited structural claims, such as a master-detail cascade delete or two flows with an undefined order. The details: routing and refusal, architecture and the trust boundary, asking questions, ADR-001 confidence-tagged edges and ADR-008 deterministic reasoning.

What you can ask

Every area answers in plain language; ask "what can you do?" for the live map.

AreaExample questions
Find & identify"where is the email field?" · "what's the payment object called?"
Understand"what does this validation rule do?" · "what happens when an Account is saved?" (automation on standard objects works even when the object itself was not retrieved; the answer says so)
Impact & dependencies"what breaks if I delete this field?" · "is it safe to deactivate this flow?"
Permissions & sharing"why can't this user see this record?" · "who can edit the Salary field?" · "who holds the Sales Manager permission set?" (live) · "what does user Jane hold?" (live) · "who's in the Support queue?" (live) · "which active users have zero permission-set assignments?" (live)
Automation & code"what runs on Case create?" · "which Apex methods have no real test coverage?" · "decode this Apex debug log / governor-limit exception to the class that ran"
Decision-support (before you build/change)"before I add automation to this object, what already runs there?" · "building Apex here — what should I watch out for?" · "before I change/require this field, what breaks?"
Architect & developer"are there circular Apex dependencies?" · "which classes have no test reference?" · "does the vault still match the live org?"
Integrations"what external systems does this org talk to?" · "list every outbound endpoint"
Documentation"give me a tour of this org" · "generate a data dictionary" · "which reports / objects / permission sets have no description?"
Health & audit"is my vault fresh?" · "where is PII stored?" · "how has the org changed across refreshes?"

All of these are read-only briefings; none of them write to the org. Every component an answer names is backed by a tool call and cited with its canonical id (CustomObject:Account, CustomField:Account.Industry__c), and every relationship with its confidence (declared, parsed or heuristic). The full catalog with the live counts comes from sfi.capabilities (through sfi.run_analysis) or the tools page; the counts are pinned by eval/product-manifest.json, never typed by hand.

What it does NOT do

Boundaries are explicit, and the product tells you plainly when it hits one rather than papering over the gap with general Salesforce knowledge:

  • Offline by default. Vault tools never call Salesforce mid-conversation. Run /sfi-refresh (or sfi refresh) to update metadata. The opt-in live tools (sfi.live_*) run read-only queries with strict caps and label their answers live_org. They stay off until you grant consent once per org with sfi.live_consent { grant: true } (bound to the org and user, scoped, expiring, stored locally) or set SFI_LIVE_PLANE_ENABLED=1. A per-call liveEnabled: true is intent only, not consent. Hybrid answers combine the vault and the live org and say so. The product never picks which org to query on its own.
  • No record-level data. The vault stores schema and source, not rows. "How many Opportunities closed last quarter" is a question for your org directly.
  • Static analysis, not runtime. Dependency edges come from metadat

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