AI infrastructure for energy teams and the LLMs they already use.

PatchOps turns energy data, regulatory records, GIS layers, SQL, and operations tools into a secure MCP platform for Claude, ChatGPT, Codex, Cursor, internal copilots, and customer-facing AI products.

Infrastructure, not templates

One MCP control plane between energy systems and AI clients.

Energy systems

Production, drilling, land, regulatory, GIS, environmental, SQL, and productivity data.

Well data
Permits and compliance
Maps and GeoJSON
Databases and docs

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

Built for the people doing the work

The product story is infrastructure first, not a guided wizard.

Energy users do not need another template maze. They need reliable access to the data and tools that answer real asset, regulatory, operational, and commercial questions inside the AI surface they are already using.

For energy operators

Give engineering, land, regulatory, and operations teams one AI-ready surface for the systems they already depend on.

For technical teams

Expose governed MCP tools without rebuilding every provider API, auth flow, map renderer, or schema contract yourself.

For AI products

Power energy copilots, service portals, and workflow apps with PatchOps as the connector and execution layer behind the scenes.

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.

PatchOps is not just a catalog page. It is infrastructure for connecting data subscriptions, public agencies, operational systems, and internal databases to AI clients through MCP.

WellDatabase
Corva
Enverus
ComboCurve
RRC
ERCOT
Snowflake
Postgres
SharePoint
Teams
EPA
USGS

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.

Start with a governed MCP endpoint, then expand into embedded agent workflows, internal copilots, and customer-facing energy AI products without rebuilding the connector layer each time.