Freshness
Updated source context
Use feeds when the agent needs current information beyond model training data and static documentation.
Agent data infrastructure
AI agent data infrastructure starts with trusted feeds.
Agent applications need more than prompts and tools. They need a data layer that knows which sources matter, what changed, and how evidence should travel through the workflow.
Synorb provides the source, Stream, Manifest, and delivery layer for teams building agents that need current context from known coverage areas.
MCP · REST · Source URLs · Stable IDs · Manifests
01 / Criteria
What should the data layer include?
For the source, schema, and delivery layer behind agent applications, the useful unit is not a loose search result. It is an object the agent can retrieve, cite, filter, store, and audit.
Grounding
Evidence stays attached
Source URLs, dates, and stable IDs help the application cite, inspect, and audit what the model used.
Delivery
MCP, REST, webhooks, and archives
Agents can explore through Core MCP. Production systems use REST and webhooks for current delivery. The live window covers the current calendar month plus the previous three full months; S3 archive exports support historical backfills and replay for older months.
02 / Shape
A Manifest is the object the agent can use.
This JSON manifest is the source-grounded object delivered through MCP or REST. It is compact enough for an agent workflow and explicit enough for an application to store, cite, and audit.
Manifest excerptJSON
{
"manifest_id": "1777525429698648000",
"headline": "Source-grounded update for an AI workflow",
"summary": "What changed, why it matters, and what source supports it.",
"source": {
"name": "Watched source",
"url": "https://source.example/update",
"published_date": "2026-06-21"
},
"delivery": {
"mcp": "https://mcp.synorb.com/mcp",
"rest": "https://api.synorb.com"
},
"tags": ["company", "topic", "source-backed"]
}
03 / Fit
Where Synorb fits in the workflow.
Use Synorb when your team already knows the sources or topics it needs to monitor, and the workflow needs current context again and again. Use search or crawling for open-ended discovery.
Agents
Pull live context
Use Synorb MCP to discover Streams, inspect details, and retrieve Manifests inside an agent workflow.
RAG
Load before prompts
Push source-grounded Manifests into retrieval stores before users ask for current answers.
Apps
Render with citations
Build dashboards, feeds, monitors, and briefings with source URLs available at display time.
FAQ
Short answers for AI builders.
What is AI agent data infrastructure?
It is the source monitoring, normalization, delivery, and provenance layer that lets agents use current external context.
What pieces does Synorb provide?
Synorb provides watched source coverage, Streams, Manifests, MCP access, REST APIs, webhooks, S3 archive exports, and provenance metadata.
Why is a data layer important for agents?
Without a reliable data layer, agents overuse search, lose citations, repeat scraping work, and struggle to explain failures.
Where does Synorb fit with app code?
Synorb supplies current source-grounded context. Your application, agent, RAG store, or dashboard decides how to route and present it.
Test
Test Synorb feeds for free.
Want to connect to Synorb's graph to test source-grounded feeds for free? Start with free test credentials, then connect through Core MCP or REST.
Free test credentialscurl
curl -s https://synorb.com/connect
Start
Give your agent fresh source-backed context.
Start with keys, then connect through Core MCP while building or REST when your application owns the workflow.