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PopNx MCPServidores MCP para quienes usan IA · explicados con palabras sencillas

sf-intelligence — Salesforce org intelligence for AI agents

de PranavNagrechaversión 0.3.3i★ –iSe ejecuta en tu computadora
Nombre en el registroio.github.PranavNagrecha/sf-intelligence

Instalar

Resumen

Descripción del creador (original en inglés)

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

Los tres pilares de PopNx MCP

Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.

Qué puedes hacer con él

Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.

  • Conexión: Se ejecuta en tu computadora
  • Transporte: stdio
  • Categoría: Marketing y redes sociales
  • Debes completar: SFI_VAULT

Instalación

Elige la app de IA que usas y copia la configuración.

Antes de instalar

Necesitas

  • npmNode.js instalado (para el comando npx)

¿Qué app usas?

Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.

Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json

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

Ejecuta esto en tu terminal

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

Completa los valores vacíos antes de ejecutarlo.

Abrir en Cursor

O copia la configuración tú

Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json

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

Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.

Abrir en VS Code

O copia la configuración tú

Pégalo en .vscode/mcp.json de tu proyecto

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

Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.

Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.

Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.

Valores que debes completar

  • SFI_VAULT obligatorio 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…

Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.

Qué puede hacer

Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.

Revisiones básicasi

Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026

  • ✓ Superada

    El creador coincide con el repo

    El nombre en el registro se verificó con la cuenta de GitHub PranavNagrecha, dueña del repo

  • … Aún sin revisar

    Sigue en mantenimiento

    Todavía no hemos leído este repo en GitHub

  • … Aún sin revisar

    Tiene licencia

    Todavía no hemos leído este repo en GitHub

  • – No aplica

    El endpoint responde

    Este se ejecuta en tu computadora; no hay endpoint en internet

  • – No aplica

    Inicio de sesión con OAuth

    Se ejecuta en tu computadora y usa ajustes locales en su lugar

  • … Aún sin revisar

    Sin instrucciones ocultas en las descripciones de herramientas

    Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet

Comparado con otros en Marketing y redes socialesi

  • Más estrellas que el 0% de los otros 2985 servidores de esta categoría
  • Publicado en el registro más recientemente que el 46% de los otros 2985 servidores de esta categoría
  • Revisiones básicas iguales o mejores que el 100% de los otros 2985 servidores de esta categoría

Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.

Preguntas frecuentes

¿Es seguro sf-intelligence — Salesforce org intelligence for AI agents?

Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.

¿Qué claves o códigos necesita?

Debes completar: SFI_VAULT

¿Se ejecuta en mi computadora o en la nube?

Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).

¿Sigue en mantenimiento?

El repo de GitHub cambió por última vez –, y la última versión (0.3.3) llegó al registro hace 34 días.

¿Qué apps pueden usarlo?

Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.

¿Qué puedo usar en su lugar?

En la misma categoría: MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer

Alternativas

Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.

Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi

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README del creador

Abrir el README

Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.

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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

Solo se muestra el principio; lee el resto en el repo

Pregunta a PopNx