langgraph-api
Decision gist · record as of 2026-08-14
Yes, if you are developing LangGraph agents and want a lightweight local testing environment with UI inspection and hot-reload. The low install friction and active maintenance make it a natural fit for the development phase. However, verify that the Elastic License 2.0 terms align with your deployment plans, and note that this is explicitly not for production use—production deployments require separate deployment options.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.11 or later.
- Intended for development/testing only; production deployments require separate deployment options backed by production-grade databases.
- Low friction: pure Python wheel with no compiled dependencies.
License · maintenance · safety
Elastic-2.0 (unclear) — Licensed under Elastic License 2.0 (license_treatment: unclear). Elastic 2.0 is a source-available license with commercial restrictions; verify compatibility with your use case before deploying in production or closed-source contexts.
last release 2026-08-13 (1 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 9,811,182 downloads/mo, #1,499 on PyPI
Alternatives
Verify before relying
pip install -U 'langgraph-cli[inmem]'
langgraph dev --config ./langgraph.json
# Server launches with browser UI; state persists in memory during session- Whether Elastic License 2.0 restrictions apply to your intended use (commercial, closed-source, or SaaS deployment).
- Performance characteristics and concurrent request limits under typical development workloads.
- Data persistence behavior across server restarts and whether local disk persistence is suitable for your testing workflow.
What it is and what it does
LangGraph API is a local development server that lets you build and test LangGraph agents with a tight feedback loop. It provides an in-memory data store (persisted to local disk on restart) and a browser-based UI for inspecting agent state, runs, and threads. The server supports hot-reload, so code changes trigger automatic restarts without losing your session context.
The package is designed for rapid iteration during development and testing—not production deployment. It depends on a large LLM-agent stack (langchain-core, langchain-protocol, langgraph, starlette, uvicorn, and observability tools like OpenTelemetry). You start it via the langgraph-cli tool with the inmem extra, point it at a langgraph.json config file, and interact with your agent through the UI or programmatically. Debugging support includes remote debugger attachment for IDE breakpoint stepping.
Use it for
- Iterate on agent logic during development with instant feedback and automatic server reload on code changes.
- Inspect agent state, thread history, and run traces through the browser UI to debug agent behavior.
- Test multi-turn conversations and agent decision-making without setting up a production database.
- Attach an IDE debugger to step through agent code line-by-line during execution.
- Prototype and validate LangGraph workflows before deploying to production infrastructure.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are developing LangGraph agents and want a lightweight local testing environment with UI inspection and hot-reload.
The low install friction and active maintenance make it a natural fit for the development phase. However, verify that the Elastic License 2.0 terms align with your deployment plans, and note that this is explicitly not for production use—production deployments require separate deployment options.
Install
langgraph-api on PyPI
Before you install
Low friction: pure Python wheel with no compiled dependencies. Active maintenance (released 2026-08-13, 1 day old). Requires Python 3.11+. Depends on 34 runtime packages including langchain-core, langgraph, starlette, and uvicorn—a substantial but standard LLM-agent stack.
Requires Python 3.11 or later. Intended for development/testing only; production deployments require separate deployment options backed by production-grade databases.
License in practice
Licensed under Elastic License 2.0 (license_treatment: unclear). Elastic 2.0 is a source-available license with commercial restrictions; verify compatibility with your use case before deploying in production or closed-source contexts.
Quickstart
pip install -U 'langgraph-cli[inmem]'
langgraph dev --config ./langgraph.json
# Server launches with browser UI; state persists in memory during sessionVerify before relying
- Whether Elastic License 2.0 restrictions apply to your intended use (commercial, closed-source, or SaaS deployment).
- Performance characteristics and concurrent request limits under typical development workloads.
- Data persistence behavior across server restarts and whether local disk persistence is suitable for your testing workflow.
Package facts
| License | Elastic-2.0 unclear |
| Python support | Supports the current Python release >=3.11 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 34 packagescloudpicklecryptographygrpcio-health-checkinggrpcio-toolsgrpciohttptoolshttpxjsonschema-rslangchain-corelangchain-protocollanggraph-checkpointlanggraph-runtime-inmemlanggraph-sdklanggraphlangsmithopentelemetry-apiopentelemetry-exporter-otlp-proto-httpopentelemetry-exporter-prometheusopentelemetry-sdkorjsonprometheus-clientprotobufpyjwtsse-starlettestarlettestructlogtenacitytruststoreuuid-utilsuvicorn |
| Maintenance | Actively maintained 1 days since the last release |
| First released | |
| Downloads | 9,811,182 / month, #1,499 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: langgraph_api-0.12.4-py3-none-any.whl
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See also langgraph-cli · langgraph-runtime-inmem · langgraph-sdk · langmem · aegra-api · uipath-langchain · langgraph-prebuilt · langgraph · langgraph-supervisor · ag-ui-langgraph