Product

One engine for inspecting, scoring, and integrating LCA data

Volca is an environmental computation product with several entry points: a hosted web UI, desktop app, self-hosted engine, HTTP API, Python client, CLI, REPL, and MCP tools for agent workflows.

What Volca includes

Use

Hosted web UI

Start in the browser: search datasets, open activities, inspect exchanges, trees, inventories, and impacts.

Use

Desktop app

Explore locally when you prefer a desktop workflow or need a local-first path before deeper deployment.

Run

Self-hosted engine

Run the open-source Volca engine yourself for controlled infrastructure, private datasets, or integration work.

Integrate

HTTP API

Call Volca from another product, dashboard, notebook, pipeline, or internal tool through a documented JSON API.

Integrate

Python client

Use pyvolca from notebooks or scripts to search, inspect, aggregate, score, and export environmental data.

Automate

CLI and REPL

Run repeatable checks, local queries, imports, method inspection, and batch-oriented workflows from the terminal.

Ask

MCP for agents

Connect AI assistants to real LCA data and computation paths instead of leaving answers detached from sources.

Extend

Own database import

Use Volca beyond public examples with custom, internal, or licensed databases where your real work happens.

Core capabilities

Search and browse

  • Search activities, products, flows, classifications, and locations.
  • Navigate multiple loaded databases without exporting everything first.
  • Open records directly from UI, API, Python, CLI, or MCP workflows.

Inspect structure

  • View direct exchanges, supply-chain trees, graph paths, and inventories.
  • Separate activity data, technosphere links, biosphere inventory, and impacts.
  • Trace why a result exists instead of treating the number as a black box.

Compute impacts

  • Compute LCIA scores over method collections.
  • Use normalization, weighting, scoring indicators, and top contributors where available.
  • Recent batch scoring improvements make large product sets practical to explore interactively.

Audit mappings

Compare and substitute

  • Compare products, methods, inventories, and contribution patterns.
  • Use substitution-aware endpoints for scenario and alternative exploration.
  • Keep comparison workflows tied to inspectable data.

Package and deploy

  • Use hosted, desktop, or self-hosted paths from the same engine.
  • Expose Volca through API, Python, CLI, REPL, or MCP surfaces.
  • Keep license visibility and deployment boundaries explicit.

Recent proof points

Performance

Batch LCIA in seconds

An EF 3.1 adapted benchmark across 911 products and 7 databases reduced the scoring phase from about 25 minutes to about 24 seconds — roughly 26 ms per product in that batch workload.

Correctness

More robust method handling

Recent engine work improves regionalized LCIA, compartment matching, location parsing, incompatible unit conversions, and openLCA JSON-LD method behavior.

Auditability

Flow-mapping diagnostics

Flow-mapping audit workflows help explain missing impacts, characterize mapping gaps, and make method coverage work more transparent.

Not sure where to start?

If you are evaluating Volca from your own problem, start with use cases. If you already know the surface you need, go directly to the product path or docs.