Freshness
Updated source context
Use feeds when the agent needs current information beyond model training data and static documentation.
LLM-ready data
LLM-ready web data should arrive with context already attached.
LLM applications spend too much effort cleaning raw pages, removing boilerplate, deduplicating updates, and trying to recover source evidence.
Synorb packages watched source updates as Manifests with Briefs, Signals, tags, source URLs, dates, and stable IDs.
MCP · REST · Source URLs · Stable IDs · Manifests
01 / Criteria
What should the data layer include?
For web-derived data shaped for LLM applications before it reaches the prompt, 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 LLM-ready web data?
It is current web context that has been normalized into a compact, source-backed object an LLM workflow can use.
What should LLM-ready data include?
It should include summaries, source URLs, dates, stable IDs, tags, provenance, and enough structure for routing or retrieval.
How does Synorb make web data LLM-ready?
Synorb watches sources, creates Manifests, attaches source metadata, and exposes those objects through MCP, REST, and webhooks.
Can LLM-ready data feed RAG systems?
Yes. Manifests can be embedded, stored, routed, or displayed downstream while keeping citations available.
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.