Oil & Gas RAG
This MCP server provides oil and gas industry data access and retrieval-augmented generation (RAG) capabilities through a Go-based backend with MySQL storage and OpenAI integration. Built with Chi router and featuring comprehensive domain-specific tools, it offers access to drilling events, production data, purchase orders, timeseries analytics, work orders, and HSSE incidents, along with document search through hybrid vector/full-text retrieval and anomaly detection using z-score analysis. The implementation includes a React frontend with real-time chat streaming, JWT-based admin authentication, Docker deployment with separate API and worker services, and MCP tool registry supporting both in-process execution and HTTP endpoints, making it valuable for petroleum engineers analyzing operational data, procurement teams tracking purchase orders, and safety personnel monitoring incidents across drilling and production operations.
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 2026-09-28.
Scan details: Circle-IR · 2026-09-28 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- database
- Source
- PulseMCP
- Repository
- github.com/kukuhtw/mcp_rag_go
- Author type
- human
- Last scanned
- 2026-09-28
- Updated
- 2026-09-28
Use via MCP
Resolve Oil & Gas RAG 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.