Context Streams
for AI agents.
The context layer for AI agents. Like Vercel KV but for agent memory. Publish interactions, query by key or vector, get materialized context. No Kafka required.
Architecture
Three layers. Real-time context. No infrastructure nightmare.
Built different
Not another Kafka. Purpose-built for AI agent context.
⚡ Instant Context
GET /context/{key} returns materialized context in milliseconds. No query building. No joins.
🔍 Vector Search
Semantic similarity powered by ScyllaDB. Find relevant past interactions, not just exact matches.
📊 Stream Processing
Benthos transforms raw messages into materialized views. Context windows, aggregations, enrichment.
🔒 Durable by Default
PostgreSQL handles ordering and durability. Your messages won't disappear.
🚀 No Ops
Deploy to Railway in minutes. No Kafka clusters. No Zookeeper. No schema registry configs.
🔌 Just HTTP
REST API. Works from any language. No client libraries required. curl it.
API Reference
Simple REST. No surprises.
| Method | Endpoint | Description |
|---|---|---|
| POST | /streams | Create a new stream with schema reference and config |
| GET | /streams | List all streams |
| GET | /streams/{name} | Get stream details |
| POST | /streams/{name}/messages | Publish a message with optional embedding |
| GET | /streams/{name}/messages | Query messages by key, time range |
| POST | /streams/{name}/search | Vector similarity search |
| GET | /streams/{name}/context/{key} | Get materialized context for a key |
Powered by boring, reliable infrastructure
Ready to stream?
Open source. MIT licensed. Deploy in minutes.