Freshness
Updated source context
Use feeds when the agent needs current information beyond model training data and static documentation.
Fresh LLM context
Fresh context for LLM apps should arrive before the prompt needs it.
LLM apps can answer from training data, uploaded docs, retrieval stores, tools, and web search. The hard part is keeping current external context ready without re-scraping every time.
Synorb turns watched source coverage into Manifests so LLM applications can use fresh, cited context through MCP, REST, and webhooks.
MCP · REST · Source URLs · Stable IDs · Manifests
01 / Criteria
What should the data layer include?
For current source-backed context for LLM 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 fresh context for LLM apps?
Fresh context is current information added to an LLM workflow so the model can reason beyond training data and stale docs.
How does Synorb keep context fresh?
Synorb watches configured sources and delivers Manifests as current source-grounded updates become available.
Can fresh context be used with RAG?
Yes. Teams can ingest Manifests into retrieval stores or call Synorb at workflow time when the app needs current evidence.
How do builders test Synorb quickly?
Use https://synorb.com/connect to self-provision Starter credentials, then call Core MCP or REST.
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.