neeshykha/sf-caseops-mcp

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Read-only Salesforce case ops as MCP tools — auth delegated to the sf CLI, agent-composable support queries

概要

A read-only MCP server that turns Salesforce case operations into tools an AI agent can call. Point Claude (Desktop or Code) at your org and ask questions in plain English: "where's the backlog right now," "show me escalated cases from this week," "created vs closed for the last month." Built from real support-ops practice: the tool surface is the set of queries a support operations manager actually runs — queue volumes, case lookups, weekly created/closed trend — not a generic API wrapper. Every tool shells out to sf, so credentials live in the CLI's keychain. The server never sees, stores, or transmits a password or token — if sf org list works, the server works. The server only wraps three subcommands: sf data query, sf sobject describe, and sf org display. None of them can modify data. On top of that, the raw SOQL tool rejects anything that isn't a SELECT, and identifier inputs (object names, case numbers, statuses) are validated before they touch a query.

README

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sf-caseops-mcp

A read-only MCP server that turns Salesforce case operations into tools an AI agent can call. Point Claude (Desktop or Code) at your org and ask questions in plain English: “where’s the backlog right now,” “show me escalated cases from this week,” “created vs closed for the last month.”

Built from real support-ops practice: the tool surface is the set of queries a support operations manager actually runs — queue volumes, case lookups, weekly created/closed trend — not a generic API wrapper.

Design decisions

Auth is delegated entirely to the sf CLI. Every tool shells out to sf, so credentials live in the CLI’s keychain. The server never sees, stores, or transmits a password or token — if sf org list works, the server works.

Read-only by construction, not by promise. The server only wraps three subcommands: sf data query, sf sobject describe, and sf org display. None of them can modify data. On top of that, the raw SOQL tool rejects anything that isn’t a SELECT, and identifier inputs (object names, case numbers, statuses) are validated before they touch a query. Giving an LLM write access to a production CRM is a decision that deserves its own design conversation — this server deliberately doesn’t open that door.

Org targeting is explicit and inspectable. Set SF_TARGET_ORG to an org alias (falls back to the sf CLI default org). The org_info tool reports which org is connected and whether it’s a sandbox, so the agent — and you — can always verify before trusting an answer.

Tools

Tool	What it does
`org_info`	Which org am I connected to? Alias, username, instance, sandbox or not
`soql_query`	Arbitrary read-only SOQL SELECT
`describe_object`	Field names, types, and picklist values for any object
`case_lookup`	Full detail on one case by number, including recent comments
`recent_cases`	Cases from the last N days, optionally filtered by status
`queue_volumes`	Open case counts by queue/owner — the “where’s the backlog” view
`case_volume_report`	Weekly created vs closed vs net, for trend spotting
`sla_risk_report`	Entitlement milestone risk: pending first-response clocks, fresh breaches, paused waiting-on-customer milestones
`problem_candidates`	Candidate problem records: Product/Type pairs recurring at one property, weekly bursts over a pair’s own baseline, slow drifts above a quarter ago, units that keep coming back

Setup

Requires the Salesforce CLI authed to at least one org, and Python 3.10+.

git clone https://github.com/neeshykha/sf-caseops-mcp
cd sf-caseops-mcp
python3 -m venv .venv && ./.venv/bin/pip install "mcp>=1.28,<2"

The version bound matters. The MCP Python SDK released v2.0.0 on 2026-07-28 alongside the stateless spec revision, and it renamed FastMCP to MCPServer,

GitHub で README 全文を見る

インストール

This server does not publish a one-line install command.

Open the repository installation guide MCP 初心者？mcpskill.org のガイドから始めましょう →

設定

{
  "mcpServers": {
    "sf-caseops": {
      "command": "/path/to/sf-caseops-mcp/.venv/bin/python",
      "args": ["/path/to/sf-caseops-mcp/server.py"],
      "env": { "SF_TARGET_ORG": "sandbox" }
    }
  }
}