Salesforce Data Cloud
MCP server implementation by CData Software that provides AI assistants with access to Salesforce Data Cloud through a generic JDBC-based architecture. Built in Java using the Model Context Protocol SDK, the implementation offers three core tools: get_tables for discovering available data objects and collections, get_columns for retrieving field metadata and data types, and run_query for executing SQL SELECT statements with results returned in CSV format. The server uses CData's JDBC driver architecture to connect to Salesforce Data Cloud, supporting dynamic discovery of database metadata including catalogs, schemas, and table structures, with configurable identifier quoting and SQL dialect handling. Designed for data analysts and developers who need programmatic access to Salesforce Data Cloud for querying customer data, building reports, or integrating Salesforce analytics into AI-powered workflows where structured data access through familiar SQL interfaces is preferred over native Salesforce APIs.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-19.
Scan details: Circle-IR · 2026-09-19 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- database
- Source
- PulseMCP
- Author type
- human
- Last scanned
- 2026-09-19
- Updated
- 2026-09-19
Use via MCP
Resolve Salesforce Data Cloud from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp --scope user for --scope project to commit it to .mcp.json.