salesforce-mcp-server
Enables AI-driven Salesforce automation and analysis without manual CLI work, reducing development friction and accelerating metadata management, code review…
MCP server that enables AI assistants to interact with Salesforce orgs through the Salesforce CLI, providing tools for Apex execution, SOQL queries, metadata management, code analysis, and development automation.
- Ask Claude to query Salesforce data using SOQL to find overdue opportunities.
- Generate Apex code snippets for custom business logic and test execution.
- Automate metadata retrieval and analysis to audit custom objects and fields.
Enables AI-driven Salesforce automation and analysis without manual CLI work, reducing development friction and accelerating metadata management, code review, and deployment cycles for orgs managing complex customizations.
Salesforce platform engineers and DevOps teams automating development workflows and metadata governance at scale.
https://github.com/advancedcommunities/salesforce-mcp-server
By advancedcommunities
How to Get It
claude mcp add salesforce-mcp-server -- npx -y salesforce-mcp-server
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
Once it’s connected, paste this into Claude:
Query Salesforce data using SOQL to find overdue opportunities
Trust Signals Auto-scanned
Data & Access
Community Pulse Quiet
No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 37 GitHub stars; contributors unknown; last commit 0d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
How to evaluate tools before deploying →
Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 37 GitHub stars; contributors unknown; last commit 0d ago; license MIT.