DEV Community

Immanuel Gabriel
Immanuel Gabriel

Posted on

Building FreshContext: Temporal Intelligence Infrastructure for AI Systems

I’ve been building something called FreshContext.

The core idea is simple:

AI systems often treat fresh and stale retrieved information as equally useful.

FreshContext is an attempt to fix that.

Instead of only retrieving information, the system applies temporal scoring before signals reach an LLM or agent workflow.

That means:

  • source timestamps matter
  • decay matters
  • provenance matters
  • retrieval timing matters

What I built so far

1. FreshContext MCP

A Cloudflare-native MCP server with 21 tools focused on freshness-aware retrieval and live intelligence workflows.

Current stack:

  • Cloudflare Workers
  • D1
  • KV
  • structured JSON envelopes
  • freshness scoring
  • observability tooling

GitHub:
https://github.com/PrinceGabriel-lgtm/freshcontext-mcp


2. Fresh HN Feed

A freshness-ranked Hacker News signal feed.

Instead of simply listing posts chronologically, the feed scores signals using temporal decay and relevance weighting.

GitHub:
https://github.com/PrinceGabriel-lgtm/fresh-hn-feed


3. Fresh Jobs Feed

A freshness-ranked jobs API built on public job sources.

The current focus is AI/ML-oriented roles, but the architecture is designed for broader signal ingestion later.

GitHub:
https://github.com/PrinceGabriel-lgtm/fresh-jobs-feed

Live API:
https://fresh-jobs-feed.gimmanuel73.workers.dev


4. Ops Pulse

One thing I learned quickly:
observability matters.

I built a separate operational analysis tool for monitoring:

  • Workers
  • D1
  • cron ingestion
  • runtime failures
  • cache behavior
  • external API failures

The biggest improvement so far wasn’t a new feature.

It was finally seeing the actual failure patterns clearly.


What surprised me

The hardest part wasn’t generating responses.

It was:

  • freshness correctness
  • runtime isolation
  • cache correctness
  • partial failure handling
  • observability
  • temporal consistency

The infrastructure side of AI systems is much deeper than I expected.


Current direction

The long-term goal is turning FreshContext into a broader temporal intelligence platform:

  • freshness-aware feeds
  • agent retrieval infrastructure
  • signal marketplaces
  • operational intelligence
  • temporal ranking APIs

Still very early.
But the architecture is finally starting to stabilize.

If you’re building retrieval systems, agents, MCP tooling, or Cloudflare-native AI infrastructure, I’d genuinely love to connect and learn from others working in this space.

Top comments (0)