FreshContext

I asked Claude to help me find a job. It gave me a list of openings. I applied to three of them. Two didn't exist anymore. One had been closed for two years.

Claude had no idea. It presented everything with the same confidence.

That's the problem freshcontext fixes.

This repository is the integrated FreshContext Core/MCP package. FreshContext is the context judgment layer between retrieval and reasoning. Core is the reusable engine that scores, ranks, explains, and turns candidate context into decision-ready context; MCP is the first live host/interface over that engine.

Live demo: freshcontext-mcp.gimmanuel73.workers.dev/demo — same model, same query, two completely different answers. Only the temporal layer changed.

The problem

Large language models retrieve web data semantically. Cosine similarity finds the documents that match a query best — but cosine doesn't know when a document was written.

So a 2022 blog post and a 2026 paper can score nearly identically. The model gets a context window full of stale documents and faithfully summarizes 2022 advice for a 2026 question.

That's not hallucination. That's correct summarization of corrupted retrieval.

Most RAG pipelines rank context correctly semantically but incorrectly temporally.

The layer

FreshContext is context integrity infrastructure for AI agents and retrieval systems. It sits between retrieval and reasoning:

candidate context
  -> FreshContext Core
  -> decision-ready context
  -> model / agent / app

FreshContext evaluates freshness, source profile, confidence, utility, provenance material, and failure honesty before context reaches the LLM. The temporal core uses Decay-Adjusted Relevancy:

R_t = R_0 · e^(−λt)

• R_0 — base semantic relevancy (whatever your retriever already gives you)
• λ — source-specific decay constant (HN ≈14h half-life, blogs ≈29d, academic papers ≈1.6y)
• t — hours elapsed since publication
• R_t — decay-adjusted relevancy at query time

That's the core correction. No model swap. No re-embedding. No re-indexing. The layer drops onto whatever retrieval pipeline you already have.

The layer is the product. The named adapters shipped with this repo demonstrate compatibility across different source classes. The DAR engine, the freshness envelope, Source Profiles, and the FreshContext Specification are the moat.

The standard

Every FreshContext-compatible response wraps content in a structured envelope:

[FRESHCONTEXT]
Source: https://github.com/owner/repo
Published: 2024-11-03
Retrieved: 2026-03-05T09:19:00Z
Confidence: high
---
... content ...
[/FRESHCONTEXT]

When it was retrieved. Where it came from. How confident we are the date is accurate.

The FreshContext Specification v1.2 is published as an open standard under MIT licence. Any tool, agent, or system that wraps retrieved data in this envelope is FreshContext-compatible. → Read the spec · Read the methodology

Architecture boundary

FreshContext Core is the reusable center of the current integrated package. It owns signal normalization, freshness scoring, Source Profiles, decision output, envelope formatting, failure guards, shared types, rank/explain primitives, and the context-conditioned utility primitive.

MCP is the primary reference/interface implementation over Core. Claude Desktop is supported, but not required. The MCP tool surface exposes named reference adapters and a live interface for using the system.

The production Cloudflare Worker now uses Core-backed envelope generation. Worker-specific concerns remain outside Core: MCP transport, runtime guards, KV cache policy, cache metadata injection, JSON parse/replace cache helpers, D1 feeds, cron, rate limiting, and Store/feed scoring/provenance.

See Core / MCP Boundary for the current package boundary and the staged path toward a future standalone Core package.

Core import path

FreshContext Core is also available directly from the current MCP package:

import {
  evaluateSignals,
  interpretEvaluations,
  getSourceProfile,
  normalizeSignal,
  calculateHaPriV2,
} from "freshcontext-mcp/core";

This is a Core subpath export inside freshcontext-mcp, not a standalone freshcontext-core package yet. The root package and freshcontext-mcp binary remain the MCP reference host.

Primary MCP interface

The clearest MCP path is evaluate_context.

It accepts candidate context from any retriever, agent, database, local script, note parser, or adapter output:

{
  "profile": "academic_research",
  "intent": "citation_check",
  "signals": [
    {
      "title": "Example source",
      "content": "Candidate context text...",
      "source": "https://example.com/source",
      "source_type": "arxiv",
      "published_at": "2026-05-24T12:00:00.000Z",
      "retrieved_at": "2026-05-24T13:00:00.000Z",
      "semantic_score": 0.92
    }
  ]
}

FreshContext returns decision-first output:

• Decision
• Meaning
• Action
• Warnings
• Source
• Freshness
• Rank score
• Utility
• Confidence
• Why

Structured results also include a readable object for humans:

{
  "decision": "cite_as_primary",
  "label": "Cite as primary",
  "readable": {
    "label": "Primary source",
    "summary": "This source is strong enough to use as main evidence.",
    "why": [
      "Strong semantic match and current freshness for arxiv.",
      "source profile academic_research uses lenient date policy",
      "intent profile citation_check selected"
    ],
    "action": "Use this as main evidence while preserving citation and provenance.",
    "warnings": [
      "FreshContext judges citation readiness and context usefulness; it does not certify truth."
    ]
  }
}

The readable object translates Core decisions into user-facing language. It does not change ranking, decision labels, utility scoring, or source intake. Utility helps explain usefulness for the current question; it remains explanatory and does not control default decision labels or ranking.

FreshContext does not certify truth. It records why context was used, supported, questioned, refreshed, watched, or excluded before it reaches a model.

evaluate_context does not fetch URLs, crawl, scrape, browse, read folders, or call adapters. It only evaluates candidate context the caller provides.

Current boundary: evaluate_context is part of the npm/local stdio MCP server prepared for 0.3.23. The hosted Cloudflare Worker MCP endpoint was last verified separately at 0.3.23 / 22 tools. The Worker remains a separate deployment surface, so future package interfaces should be re-verified remotely before being claimed live.

Network Boundary

FreshContext's primary evaluate_context path does not fetch, crawl, scrape, browse, read folders, or call adapters. The MCP package also includes read-only reference adapters that use network access only when those adapter tools are invoked. Supply-chain scanners may therefore report package network access; that applies to the optional adapter surface, not to caller-provided context evaluation.

Advanced Worker/feed surface

Beyond the per-call Core/MCP paths, the production Worker deployment exposes a continuous, decay-scored, deduplicated feed. This is an advanced deployment surface, not the required way to use FreshContext Core:

GET /v1/intel/feed/:profile_id?limit=20&min_rt=0

Every signal is stamped with base_score, rt_score, entropy_level (low / stable / high), ha_pri_sig (Ha-Pri v1 SHA-256 provenance reference), semantic_fingerprint (cross-adapter dedup), and published_at. Ready for direct LLM or agent consumption — no synthesis required.

Production endpoint: https://freshcontext-mcp.gimmanuel73.workers.dev

Reference adapters

The repo ships named reference adapters that demonstrate how different source classes can become FreshContext-compatible. Each adapter keeps its own name because it represents a source boundary; the adapter count is operational proof, not the product headline.

Intelligence

Competitive research

Market data

Composites — multiple sources, one call

Official, regulatory, and procurement sources

Quick start

For Claude Desktop, Codex, npx, global npm, and source-checkout setup, see the concise client setup guide.

Cloud (no install)

Add to your Claude Desktop config and restart:

Mac: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "freshcontext": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://freshcontext-mcp.gimmanuel73.workers.dev/mcp"]
    }
  }
}

Restart Claude. Done.

Prefer a guided setup? Visit freshcontext-site.pages.dev — 3 steps, no terminal.

Local (full Playwright)

Requires: Node.js 20+ (nodejs.org)

git clone https://github.com/PrinceGabriel-lgtm/freshcontext-mcp
cd freshcontext-mcp
npm install
npx playwright install chromium
npm run build

Add to Claude Desktop config:

Mac:

{
  "mcpServers": {
    "freshcontext": {
      "command": "node",
      "args": ["/Users/YOUR_USERNAME/path/to/freshcontext-mcp/dist/server.js"]
    }
  }
}

Windows:

{
  "mcpServers": {
    "freshcontext": {
      "command": "node",
      "args": ["C:\\Users\\YOUR_USERNAME\\path\\to\\freshcontext-mcp\\dist\\server.js"]
    }
  }
}

Mac troubleshooting

"command not found: node" — Use the full path:

which node  # copy this output, replace "node" in config

Config file doesn't exist:

mkdir -p ~/Library/Application\ Support/Claude
touch ~/Library/Application\ Support/Claude/claude_desktop_config.json

Usage examples

The npm run demo:* commands below are source-checkout workflows for contributors and evaluators using a cloned repository. The published npm package is the MCP server/runtime package and does not include repo-only source examples or tests.

From an installed npm package, the supported runtime entrypoints are npm start and the freshcontext-mcp binary. Repo-only scripts such as tests, demos, smoke checks, and trust scans print a source-checkout notice when their source files are not present.

The Apify Actor entrypoint remains available in the source checkout for separate actor packaging, but it is intentionally not part of the published MCP npm runtime package.

Release trust gate

Run the local release gate before a release, package review, demo, or PR review:

npm run trust:gate

The gate runs the Trust Scanner with repo-map reporting, npm package-boundary inspection, deterministic claim checks, and --fail-on fail. It is local-only, does not publish or deploy, does not send telemetry, and does not replace dedicated security scanners.

Generate review reports when you need a shareable summary:

npm run trust:report
npm run trust:report:json

To write a Markdown report file explicitly:

npm run trust:report -- --output TRUST_SCAN_REPORT.md

Bring your own source list

FreshContext can evaluate candidate context you provide as a local JSON file:

npm run demo:evaluate:file

To pass a different file:

npm run demo:evaluate:file -- path/to/sources.json

Included examples:

npm run demo:evaluate:file -- examples/sources.academic.example.json
npm run demo:evaluate:file -- examples/sources.jobs.example.json

Minimal shape:

{
  "profile": "academic_research",
  "intent": "citation_check",
  "signals": [
    {
      "title": "...",
      "content": "...",
      "source": "...",
      "source_type": "arxiv",
      "published_at": "...",
      "retrieved_at": "...",
      "semantic_score": 0.92
    }
  ]
}

This local demo does not fetch URLs, crawl, or read folders. It evaluates candidate context you provide and returns decision-first output: Decision, Meaning, Action, Warnings, and supporting metrics.

In an MCP client, use evaluate_context when you already have candidate context from another retriever, database, agent, or script:

Use evaluate_context with profile "academic_research", intent "citation_check", and these candidate signals: [...]

Use the named reference adapters when you want FreshContext's current MCP package to fetch public source examples for you.

Should I build this idea?

Use extract_idea_landscape with idea "procurement intelligence saas"

Returns funding signal, pain signal, crowding signal, market signal, ecosystem signal, and launch signal — all timestamped.

Full company intelligence in one call:

Use extract_company_landscape with company "Palantir" and ticker "PLTR"

SEC filings + federal contracts + global news + changelog + market data.

Did that company just disclose something material?

Use extract_sec_filings with url "Palantir Technologies"

8-K filings are legally mandated within 4 business days of any material event — CEO change, acquisition, breach, major contract.

Is this dependency still actively maintained?

Use extract_changelog with url "https://github.com/org/repo"

Returns the last 8 releases with exact dates. If the last release was 18 months ago, you'll know before you pin the version.

Deployment & infrastructure

The reference implementation runs on Cloudflare's global edge:

• D1 database — 18 watched queries running on 6-hour cron with relevancy scoring
• KV-backed rate limiting — 60 req/min per IP across all edge nodes
• Defensive valves — clock-skew rejection (5min tolerance), hard floor at R_t<5, lazy decay at read time
• Provenance — Ha-Pri v1 SHA-256 provenance stamps on stored signals; hard tamper enforcement is a future Ha-Pri v2 path
• Schema migrations — promise-gated, idempotent, run on first request after deploy

Production: https://freshcontext-mcp.gimmanuel73.workers.dev

Roadmap

• FreshContext Specification v1.2 published (MIT, open standard)
• DAR engine with source-specific lambda constants
• Ha-Pri v1 provenance signatures on stored signals
• Semantic deduplication via fingerprinting
• Live before/after demo at /demo
• METHODOLOGY.md — methodology and engineering documentation
• Named reference adapters across intelligence, competitive research, market data, and composites
• Generic MCP evaluate_context tool for caller-provided candidate context
• Core-backed envelope generation shared by npm/MCP and the Cloudflare Worker
• Cloudflare Workers deployment — global edge, KV cache, KV rate limiting
• Published on npm and listed for MCP usage; Apify/feed assets are separated from the normal MCP runtime package
• Ha-Pri v2 Core helper and deterministic golden vectors
• Ha-Pri v2 production-enforcement design document
• Ha-Pri v2 Worker/D1 production enforcement
• GitHub Actions release workflow — manual or v* tag-triggered npm publish path
• Webhook triggers — push high-entropy signals on threshold
• Dashboard — React frontend for the D1 intelligence pipeline
• GKG upgrade for extract_gdelt — tone scores, goldstein scale, event codes

Future work is organized in FreshContext Future Lanes. Roadmap items are not live product claims until implemented and validated.

Contributing

PRs welcome. The highest-value contributions improve the caller-provided context path, decision output, host integrations, and FreshContext-compatible signal quality. New reference adapters are useful when they preserve source boundaries and emit timestamped, failure-honest context — see src/adapters/ for examples and FRESHCONTEXT_SPEC.md for the compatibility contract.

If you're building something FreshContext-compatible, open an issue and we'll add you to the ecosystem list.

Trust and security

• LICENSE
• SECURITY.md
• NOTICE.md
• TRADEMARKS.md
• Dependency diligence notes
• Release integrity notes
• Release notes

License

MIT

Built by Prince Gabriel — Grootfontein, Namibia 🇳🇦 "The work isn't gone. It's just waiting to be continued."

Also on: MCP Registry · npm