Store, Observe, Learn

The context data platform for production agents

Multi-modal Storage·Task Monitoring·Pattern Learning

Identify successful execution patterns through the Store → Observe → Learn → Act loop, so agents act smarter and succeed more over time.

Cloud Platform

Open source

┌─[ACONTEXT]─────[Context Storage API]
# Create session with user association
session = client.sessions.create(user="alice@acme.com")
# Store messages - auto-converts between providers
client.sessions.store_message(
    session_id=session.id,
    blob={"role": "assistant", "content": "..."},
    format="openai" # openai | anthropic | gemini
)
# Upload files to S3-backed disk
client.disks.artifacts.upsert(
    disk.id, file=FileUpload(...),
    file_path="/docs/"
)
# Search with glob & regex patterns
client.disks.artifacts.glob_artifacts(
    disk.id, query="**/*.md")
💬
Sessions
Store and retrieve messages across OpenAI, Anthropic, and Gemini formats with automatic conversion.
OpenAIAnthropicGeminiMulti-modal
📦
Disk & Artifacts
S3-backed file storage with glob and regex search. Upload, download, and manage agent artifacts.
Glob searchRegex grepMetadata

Context Data Platform for Self-learning Agents

Everything you need to build, deploy, and scale production-ready AI agents

Sandbox Skills

Enable agents to practice and learn in isolated environments. Capture successful tool-calling patterns and transform them into reusable skills.

Context Engineering

Reduction, Compression, Offloading, Claude skills …… all in one backend

Artifact Disk

Filesystem-like workspace to store and share multi-modal outputs (.md, code, reports), ready for multiple agents collaboration.

Open Source

Architecture built on community standards. Every major dependency has a direct open-source alternative to ensure stack portability.

Multimodal Context Storage

Unified, persistent storage for all agent data, eliminating fragmented backends (DB, S3, Redis).

Background Observer

An intelligent scratchpad for long-running tasks, trace agent status and success rates in real-time.

SDKs & Integrations

Ready to use with OpenAI, Anthropic, LangGraph, Agno, and other popular agent frameworks

Acontext Sessions

Store · Retrieve · Multi-Provider Format

Store and retrieve context in OpenAI, Anthropic, or Gemini format with one simple API.

from acontext import AcontextClient
 
client = AcontextClient()
 
# Create a session
session = client.sessions.create()
 
# Store messages (OpenAI format)
client.sessions.store_message(session.id, blob={"role": "user", "content": "Hello!"})
 
# Retrieve in any format: openai, anthropic, gemini
messages = client.sessions.get_messages(session.id, format="anthropic")

# Get token-efficient session summary for prompt injection
summary = client.sessions.get_session_summary(session.id, limit=5)
 
# Apply edit strategies to manage context window size
result = client.sessions.get_messages(
    session.id,
    edit_strategies=[
        {"type": "remove_tool_result", "params": {"keep_recent_n_tool_results": 3}},
        {"type": "token_limit", "params": {"limit_tokens": 30000}}
    ]
)
print(f"Tokens: {result.this_time_tokens}")

Reinvent the Wheel for Each Provider

Focus on creating, not adapting.

1 / 4 · Context Engineering

Join the Community

Connect with early builders & preview new features

Join Discord

Star on GitHub