MCP.Market

FreshContext MCP server

online · 100% uptime
by PrinceGabriel-lgtm·io.github.PrinceGabriel-lgtm/freshcontext·v0.5.3·12 stars
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Context integrity for AI agents: evaluate freshness, confidence, provenance, and decision readiness.

B81/100grade B
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Safety scan
B81/100

full report

Adoption
Growing

12 stars184 downloads/wk

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FreshContext tools (22, 1 write)

write = sends, deletes, buys or posts
  • evaluate_contextFree

    Evaluate caller-provided candidate context and return decision-ready output. This is the primary FreshContext judgment path: it does not fetch, crawl, scrape, browse, read folders, or call adapters.

  • extract_arxivFree

    Search arXiv for research papers via the official API. Pass a topic or full arXiv API URL. Returns titles, authors, dates, abstracts.

  • extract_changelogwrite actionFree

    Update history for any product. Accepts a GitHub repo URL or an npm package name. Returns version numbers, release dates, and entries.

  • extract_company_landscapeFree

    Most complete single-call company intelligence: SEC 8-K filings + USASpending federal contracts + GDELT global news + product changelog + Stooq quote data. 5 unique sources.

  • extract_financeFree

    No-key stock quote data via Stooq. Accepts comma-separated ticker symbols and returns quote/OHLC/volume observations with timestamps.

  • extract_finance_landscapeFree

    Composite financial intelligence: Stooq quote data + HN sentiment + Reddit discussion + GitHub ecosystem + product changelog. 5-source unified report.

  • extract_gdeltFree

    Global news intelligence from GDELT. Monitors news from every country in 100+ languages, updated every 15 minutes. Returns articles with source country, language, date.

  • extract_gebizFree

    Singapore Government procurement opportunities (GeBIZ via data.gov.sg). Search by keyword, agency name, or empty for all recent tenders.

  • extract_githubFree

    Extract real-time data from a GitHub repository — README, stars, forks, last commit, topics. Returns timestamped freshcontext.

  • extract_gov_landscapeFree

    Composite government intelligence: federal contract awards (USASpending) + dev community awareness (HN) + GitHub repo activity + product release velocity (changelog). 4-source unified report.

  • extract_govcontractsFree

    US federal contract awards from USASpending.gov. Search by company name (e.g. 'Palantir'), keyword, or NAICS code. Returns amounts, dates, agencies.

  • extract_hackernewsFree

    Extract top stories or search results from Hacker News. The url field accepts an HN/Algolia URL or a plain search query.

  • extract_idea_landscapeFree

    Idea validation composite: HN pain signals + YC funded competitors + GitHub crowding + jobs market signal + npm/PyPI ecosystem + Product Hunt launches. 6 sources.

  • extract_landscapeFree

    Composite tool. Queries GitHub + HN + npm simultaneously. Returns a unified landscape report with each source's own freshness.

  • extract_producthuntFree

    Extract recent Product Hunt launches by keyword/topic search or a PH URL. Returns name, tagline, votes, comment count, topics, and launch date per result.

  • extract_redditFree

    Extract recent posts from a subreddit (e.g. 'r/MachineLearning') or a Reddit search/listing URL. Returns title, subreddit, author, score, comment count, and post date per result.

  • extract_scholarFree

    Extract research results (title, authors, year, snippet) from a Google Scholar search URL. Scholar exposes only the publication year, not an exact date, so freshness confidence is capped at medium.

  • extract_sec_filingsFree

    SEC 8-K filings via EDGAR full-text search. 8-K = legally mandated material event disclosures (CEO changes, M&A, breaches). Pass company name, ticker, or keyword.

  • extract_ycFree

    Withdrawn in 0.5.3 pending review of source terms. Returns an error; kept so existing clients get a clear answer.

  • package_trendsFree

    npm and PyPI package metadata — version history, release cadence, last updated.

  • search_jobsFree

    Search for real-time job listings with freshness badges on every result. Sources: Remotive + HN Who is Hiring.

  • search_reposFree

    Search GitHub for repositories matching a keyword. Returns top results by stars.

Public scan report

scanner v0.1.10 · 2026-10-31 · same rubric, same numbers if you re-run it

1 high
  • Code scan82 source files scanned25/25
  • Live reliabilityremote reachable in 1021ms20/20
  • Tool poisoning22 tool descriptions checked15/15
  • Auth qualityopen endpoint exposes 1 write-action tools with no auth3/15
  • Maintenancelast push 31 days ago12/15
  • Maintainer identityregistry namespace matches repository owner6/10

Findings (1)

  • highWrite-action tools reachable without authenticationauth.open-write
Overall 81/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How FreshContext compares

Against every graded MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
81/100
higher than 62% of 48,255 servers
Tools
22
the typical server has 7
Tools that change things
5%
typical: 0%. Fewer write tools means less an agent can break
Uptime
100%
of our recent checks; the typical remote server answers 100%
Response time
164 ms
faster than 70% of 30,031 servers
GitHub stars
12
more than 89% of 28,688 servers
Downloads a week
184
more than 74% of 12,191 servers with a package

What its tools let an agent do: 20 read · 1 change · 1 run or deploy

Release history: 3 versions in the registry since 2026-05-13, latest 2026-09-27, typically one every 131 days.

Install FreshContext in Claude Code, Cursor or VS Code

claude mcp add --transport http freshcontext https://api.freshcontext.dev/mcp
Add to Cursor

What the publisher says

From the FreshContext repository's README, as published. We do not edit it. Read it on GitHub

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.

Category: context integrity infrastructure. FreshContext sits between context acquisition and agent action. Its job is to decide whether information entering an AI workflow is still fresh, attributable and coherent enough for the system to rely on. Core is the reusable engine that scores, ranks, explains and turns candidate context into decision-ready context, with signed verdicts recorded in a verifiable ledger. MCP is the first live host interface over that engine — one interface over the methodology, not the product itself.

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

Integrate it into an existing stack: freshcontext.dev/integration — start with one bounded RAG, agent, retrieval, or governance workflow and objective acceptance criteria.

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

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

FreshContext: common questions

Is FreshContext MCP server safe?
Mostly: it is graded B (81/100). Read the FreshContext safety report
How do I install FreshContext?
It runs remotely at api.freshcontext.dev. Add it to Claude Code, Cursor, VS Code or Claude Desktop with the snippets above, or call it through the mcp.market gateway without installing anything.
Does FreshContext need an API key?
Not as far as the registry entry and our scan can tell: no credentials are declared or required.
Is FreshContext maintained?
The last commit was 35 days ago (2026-09-30). The latest release is v0.5.3.
Is FreshContext up?
100% of our last 28 checks got an answer. We check remote servers about four times a day.
How does FreshContext compare with other MCP servers?
safety score 81/100 (higher than 62% of 48,255 servers); tools 22 (the typical server has 7); tools that change things 5% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.