Agentflow is now 10xGraph

Agentflow is now 10xGraph. The framework, the MIT license and the maintainers stay the same. The name changes because it was hard to find: many unrelated projects share the Agentflow name, and a search for it returns a Stanford research project, a Flowise feature and several other repositories before it returns ours. A name people cannot search for is a real cost for an open-source project, so we changed it.

What 10xGraph is

Other frameworks give you the graph. 10xGraph gives you the graph and the production server around it, open source.

You write a Python agent as a graph of nodes and tools. From the same install you get the server that runs it: REST, streaming and WebSocket endpoints, JWT or custom auth, scoped authorization on every endpoint, thread ownership, rate limiting, and Docker Compose and Kubernetes files. The tagline is “10xGraph by 10xScale: graph engineering for production AI agents.”

The five pillars

1. The production server ships in the box. The API server, auth, rate limits and deployment files come with the framework under the MIT license, not as a separate product. See Serving agents and Production runtime.
2. Correct under failure. Tool calls are replay-safe: if a process dies mid-run, a tool that already finished is not executed again, so a resumed run does not charge a card twice. Durable writes are versioned, and nodes and tools have real timeouts. Read Replay-safe tools and the engineering post Your agent charged the card twice.
3. Built to scale. Active thread state is cached in Redis for fast reads, while full history lives in PostgreSQL. Events can be published to Kafka, Redis Pub/Sub, RabbitMQ or OpenTelemetry. See Checkpointing and threads and Memory and store.
4. One stack, from backend to frontend. A typed TypeScript client covers invoke, stream, threads, memory and files, and tools can run in the user’s browser. See Connecting clients and Remote tools.
5. You own it. MIT licensed, self-hosted, and not tied to one model vendor. It works with OpenAI, Google Gemini, Anthropic and any OpenAI-compatible endpoint. See Providers.

Graph orchestration, tool-calling loops, MCP and streaming are in there too, but every serious framework has those. The pillars above are why you would pick this one.

What stays the same

• The project and the people. Same code base, same maintainers, same license: MIT, made by 10xScale.
• Configuration keys. The keys in the configuration file stay the same. Only the file name changes, from agentflow.json to 10xgraph.json.
• Your existing code keeps running. from agentflow import StateGraph still works: agentflow stays importable as a deprecated alias until 2.0. New code should import from tenxgraph, as in from tenxgraph import StateGraph.

What changes

Before	After
pip install 10xscale-agentflow	pip install 10xgraph
from agentflow import StateGraph	from tenxgraph import StateGraph
pip install 10xscale-agentflow-cli	pip install 10xgraph-api
npm install @10xscale/agentflow-client	npm install 10xgraph-client
CLI command agentflow	CLI command 10xgraph
Config file agentflow.json	Config file 10xgraph.json
GitHub organization 10xHub	GitHub organization 10xGraph

Version 0.10.0 is the final release of 10xscale-agentflow on PyPI. New releases and fixes go to the new package names.

Honest weak spots

You should know where we are behind before you choose us.

• Pre-1.0. The API can still change between minor releases. Pin versions and read the changelog.
• A smaller community. There are fewer integrations, tutorials and answered questions than for LangGraph or CrewAI.
• The rename resets recognition. 10xGraph has no search history yet, so existing blog posts and answers still say Agentflow.
• Visual tooling is lighter. LangGraph has a stronger visual studio and hosted tracing. We have a React playground and OpenTelemetry, Logfire and LangSmith publishers.
• Python 3.12 or newer, and code-first. This is not a no-code builder.

The roadmap lists what is missing or partial.

Next steps

• New to the project: follow Get started or the beginner path.
• Moving an existing install: read Installation and the changelog.
• Choosing between frameworks: see the comparisons.
• Questions or bugs: see Support, or the maintainers page for who to contact.