Energy systems
Production, drilling, land, regulatory, GIS, environmental, SQL, and productivity data.
Well data
Permits and compliance
Maps and GeoJSON
Databases and docs
AI infrastructure for energy teams and the LLMs they already use.
Energy data, records, GIS, and SQL as secure MCP tools for Claude, ChatGPT, and your own AI products.
Remote MCP
One governed MCP endpoint
100+ sources
Energy, GIS, SQL, and ops systems
LLM ready
Built for analysts, engineers, and agent apps
Infrastructure, not templates
One MCP control plane between energy systems and AI clients.
PatchOps MCP platform
A secure control plane that turns energy systems into discoverable, validated MCP tools.
OAuth and PAT access
Tool routing
Argument validation
Usage controls
LLMs and agent apps
Use the same infrastructure inside consumer LLMs, developer tools, internal copilots, and customer apps.
Claude
ChatGPT
Codex
Cursor and custom agents
Consumer LLM ready
Bring energy tools into everyday AI conversations.
Claude
Find active wells near this lease block and summarize regulatory exposure.
PatchOps routes across well data, RRC records, GIS layers, and environmental context.
Codex
Build a daily basin activity report from the connected provider APIs and SQL tables.
PatchOps supplies authenticated tools, schemas, and execution guardrails.
Customer app
Show offset production, permits, and nearby infrastructure for a planned pad.
PatchOps returns structured data, maps, and tool outputs through the same MCP layer.
How teams plug in
1
Connect private providers, public datasets, databases, and productivity systems.
2
Publish one governed PatchOps MCP endpoint with the tools each team or product can use.
3
Use it from LLM clients, local dev tools, the PatchOps CLI, SDKs, or your own agent interface.
PATCHOPS_MCP_URL=https://patchops.ai/mcp/{instance}
client.connect(PATCHOPS_MCP_URL)
tools.call("patchops_renderGeoJSON", args)Energy connector graph
A platform layer across the energy data stack.
Data subscriptions, public agencies, operational systems, and databases — connected to AI clients through MCP.
Governed access
OAuth metadata discovery
Personal access tokens
Credential isolation
Revocable endpoints
Agent-grade execution
Schema-first tools
Validated arguments
Code execution
Structured results
Energy context
Oil and gas connectors
Regulatory datasets
GIS and map rendering
Environmental layers
PatchOps MCP
Make PatchOps the infrastructure layer for energy AI.
One governed MCP endpoint — then copilots, agents, and customer-facing energy AI on the same connector layer.