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116524e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 | # Integrations Overview
ACE provides both runners and step-based integrations for popular agentic
frameworks. Some integrations are full runners, while others are composable
pipeline steps you can drop into a custom `Pipeline`.
## Available Integrations
| Runner | Framework | Input | Insight Level |
|--------|-----------|-------|--------------|
| [`ACELiteLLM`](litellm.md) | LiteLLM (100+ providers) | Questions | Micro |
| [`LangChain`](langchain.md) | LangChain Runnables | Chain inputs | Meso |
| [`BrowserUse`](browser-use.md) | browser-use | Task strings | Meso |
| [`ClaudeCode`](claude-code.md) | Claude Code CLI | Task strings | Meso |
| [`Claude SDK`](claude-sdk.md) | Anthropic Python SDK | Task strings or `ACESample` | Meso |
| [OpenClaw](openclaw.md) | OpenClaw transcripts | JSONL trace files | Meso |
| [MCP Server](mcp.md) | MCP (stdio) | Tool calls | Micro |
| [MCP Client Setup](mcp-client-setup.md) | Claude Code, Cursor, Windsurf | — | Setup Guide |
| [Opik](opik.md) | Opik observability | — | Monitoring |
| [Tracing](tracing.md) | Kayba tracing SDK | `@trace` / `start_span` | Cloud |
| [Hosted API](hosted-api.md) | Kayba hosted API | Trace files | Cloud |
## The Pattern
All integration runners follow the same three-step pattern:
```
1. INJECT — Add skillbook strategies to the agent's context
2. EXECUTE — Run the external agent normally
3. LEARN — Reflector + SkillManager update the skillbook
```
## Quick Construction
Every runner offers a `from_model()` factory that builds ACE roles automatically:
```python
from ace import BrowserUse, LangChain, ClaudeCode
# Browser automation
browser = BrowserUse.from_model(browser_llm=my_llm, ace_model="gpt-4o-mini")
# LangChain chain/agent
chain = LangChain.from_model(my_runnable, ace_model="gpt-4o-mini")
# Claude Code CLI
coder = ClaudeCode.from_model(working_dir="./project", ace_model="gpt-4o-mini")
```
For direct Anthropic API usage without a runner, compose the SDK steps directly:
```python
from ace import Pipeline, Reflector, SkillManager, Skillbook, learning_tail
from ace.integrations import ClaudeSDKExecuteStep, ClaudeSDKToTrace
skillbook = Skillbook()
pipe = Pipeline([
ClaudeSDKExecuteStep(model="claude-sonnet-4-20250514"),
ClaudeSDKToTrace(),
*learning_tail(Reflector("gpt-4o-mini"), SkillManager("gpt-4o-mini"), skillbook),
])
```
## Shared Features
All runners share these capabilities:
- **Skillbook persistence** — `save()` / load via `skillbook_path`
- **Checkpointing** — automatic saves during long runs
- **Deduplication** — prevent duplicate skills
- **Background learning** — `wait=False` for async learning
- **Progress tracking** — `learning_stats` property
## Which Integration Should I Use?
- **Building a Q&A or reasoning agent?** Use [ACELiteLLM](litellm.md)
- **Have an existing LangChain chain or agent?** Use [LangChain](langchain.md)
- **Automating browser tasks?** Use [BrowserUse](browser-use.md)
- **Running coding tasks with Claude Code?** Use [ClaudeCode](claude-code.md)
- **Calling Anthropic directly from your own pipeline?** Use [Claude SDK](claude-sdk.md)
- **Want to monitor costs and traces?** Add [Opik](opik.md)
- **Learning from OpenClaw session transcripts?** Use [OpenClaw](openclaw.md)
- **Exposing ACE as an MCP tool provider?** Use the [MCP Server](mcp.md) and the [MCP Client Setup](mcp-client-setup.md) guide
- **Want to send traces to Kayba from your code?** Use [Tracing](tracing.md)
- **Want to use the hosted API instead of running locally?** Use the [Hosted API](hosted-api.md) CLI
- **Using a different framework?** See the [Integration Guide](../guides/integration.md) to build a custom runner
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