Software Alternatives & Startups

Detectify VS ContextForge.dev

Compare Detectify VS ContextForge.dev and see what are their differences

Detectify

Detectify provides a user friendly and thorough web security scan that allows you to focus 100% on web development.

Rating
0 reviews
ContextForge.dev

Stop re-explaining your project to Claude every session. ContextForge adds persistent memory to Claude Code, Cursor, and Copilot via MCP. Free tier, 3-minute setup.

Rating
0 reviews
Pricing
Freemium $9 / Monthly (Pro — 15k queries/mo, 5 collaborators)
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Which is more popular?

Based on our record, Detectify should be more popular than ContextForge.dev. It has been mentioned 4 times since March 2021.

social mentions
4 vs 2
Cyber Security popularity
100% vs 0%
alternatives listed
240+ vs 2

Base details

Website, pricing, platforms and company facts side by side.

Detectify
ContextForge.dev
Website detectify.com contextforge.dev
Pricing
Freemium $9 / Monthly (Pro — 15k queries/mo, 5 collaborators) Official pricing
Platforms —
SaaS Web Mac Windows Linux +2
Company Startup from Sweden · 10 - 19 employees · 2012 Startup from the United States · 2026
Listed in

About Detectify and ContextForge.dev

In their own words, as submitted to SaaSHub.

Detectify
ContextForge.dev

No description of Detectify yet.

ContextForge is persistent, searchable memory for AI coding agents — built on the Model Context Protocol (MCP). Your AI assistant forgets everything when the session ends. ContextForge fixes that: save architectural decisions, naming conventions, and debugging context once, and any MCP client...

Read more about ContextForge.dev

Features and specs

What each product offers, as listed by its team.

Detectify 6 features
ContextForge.dev 6 features
  • Comprehensive Security Analysis
    Detectify offers a wide range of security scanning features that allow users to identify vulnerabilities in their web applications thoroughly.
  • Automated Scanning
    Detectify automates the vulnerability scanning process, reducing the need for manual intervention and allowing for more efficient security management.
  • Regular Updates
    The platform is continuously updated with the latest security vulnerabilities, ensuring that users are protected against emerging threats.
  • Easy Integration
    Detectify can be easily integrated into existing workflows and tools, which makes it convenient for teams to incorporate it into their development pipelines.
  • User-friendly Interface
    The platform is designed with a user-friendly interface that makes it accessible for users with varying levels of technical expertise.
  • Detailed Reports
    Detectify provides detailed reports on vulnerabilities that include descriptions, risk levels, and remediation steps to help users address issues efficiently.

Possible disadvantages

  • Cost
    For small businesses or individual developers, the cost of using Detectify may be prohibitive compared to other tools available on the market.
  • Limited Customization
    Although Detectify provides comprehensive scanning features, some users may find the customization options for scanning and reporting to be limited.
  • False Positives
    As with many automated scanning tools, Detectify may produce false positives, which can require additional time and resources to verify and resolve.
  • Depends on External Knowledge Base
    Detectify relies on its external database for identifying vulnerabilities. This means any delays or issues in updates might impact the timely identification of new threats.
  • Network Scan Limitations
    Detectify focuses primarily on web application security, which may not fully address network-level vulnerabilities or provide holistic infrastructure security.
  • Semantic Search
    Vector search (pgvector) — recall by meaning, not keywords
  • Git Integration
    Auto-ingests commits and PRs as searchable knowledge
  • MCP-Native
    Works with Claude Code, Cursor, Copilot, ChatGPT, Windsurf
  • Task Tracking
    Work items your agent can read, create, and update
  • Snapshots
    Version and restore your entire knowledge base
  • Team Sharing
    Shared spaces and memory across your team

Analysis

An editorial look at what each product does well and who it suits.

Detectify
ContextForge.dev

No analysis of Detectify yet.

Overall verdict

  • I don't have verified, specific information about ContextForge.dev, so I can't confirm its quality, features, or reputation with confidence. It may be a legitimate niche developer tool, but you should independently verify it before relying on it.

Why this product is good

  • I have no reliable data on this specific domain's product, pricing, reviews, or track record
  • The name suggests it may relate to 'context' management for AI/LLM development, but this is speculative
  • Unverified tools can carry risks around data security, support quality, and long-term viability
  • Small or new dev tool sites can be legitimate but lack the review history needed for a confident assessment

Recommended for

  • Users who independently research and verify the site's legitimacy first
  • Developers curious about niche AI/context-management tools who are comfortable testing new services
  • Not recommended for critical production use without due diligence, given the lack of verifiable information

Videos

Walkthroughs and reviews on video.

Detectify 3 videos + Add
ContextForge.dev 3 videos + Add

Detectify Crowdsource | Meet the Hacker-Gerben Janssen van Doorn

More videos

  • - Detectify Demo: Get started with Detectify
  • - A complete video walkthrough of the Detectify tool

How to Make Claude Run Automated Workflows (ContextForge Skills Tutorial)

More videos

  • - Schedule AI Prompts on a Cron with ContextForge Routines
  • - Your AI Assistant Forgets Everything — Here's the Fix MCP Memory

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
Detectify
ContextForge.dev
100% 100%
0% 0%
0% 0%
100% 100%
100% 100%
0% 0%
0% 0%
100% 100%

Questions & Answers

As answered by people managing Detectify and ContextForge.dev.

What makes your product unique?

ContextForge.dev's answer:

ContextForge is memory that lives at the MCP layer, so it works across every AI coding agent at once — Claude Code, Cursor, GitHub Copilot, ChatGPT, and Windsurf — not just one. Save a decision once and any client recalls it later with semantic search. It goes beyond a note store: automatic git sync turns your commits and PRs into searchable knowledge, plus task tracking, snapshots, and team sharing — all through a single MCP server you add with one command.

Why should a person choose your product over its competitors?

ContextForge.dev's answer:

Most memory tools are tied to a single agent or are just a key-value store. ContextForge is MCP-native, so it's portable across all your AI tools; it adds git sync so your codebase history becomes searchable context automatically; and it includes team features (shared spaces, collaborators) that solo-memory tools lack. Setup is one command, there's a genuine free-forever tier with no credit card, and paid plans start at just $9/month.

How would you describe the primary audience of your product?

ContextForge.dev's answer:

Software developers and engineering teams who use AI coding assistants — Claude Code, Cursor, GitHub Copilot, ChatGPT, Windsurf — and are tired of re-explaining their project, architecture, and conventions every session. It fits solo developers working across multiple projects as well as small teams that need shared, persistent context.

What's the story behind your product?

ContextForge.dev's answer:

ContextForge was born from a simple frustration: AI coding agents forget everything the moment a session ends. Every new conversation meant re-explaining the same architecture, naming conventions, and past decisions. ContextForge was built to give AI agents a permanent, searchable memory through the Model Context Protocol — so knowledge is captured once and reused forever, across sessions and projects. It even dogfoods its own memory to help build itself.

Which are the primary technologies used for building your product?

ContextForge.dev's answer:

Next.js 16 (App Router), React and Tailwind CSS for the dashboard, hosted on Vercel. Supabase (PostgreSQL) with pgvector powers the semantic vector search, and Deno edge functions serve the API. Embeddings use OpenAI text-embedding-3-small. The MCP client is a Node.js package (contextforge-mcp) on npm, implementing the Model Context Protocol.

User comments

Share your experience with using Detectify and ContextForge.dev. For example, how are they different and which one is better?

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Social recommendations and mentions

Recommendations tracked on public social media and blogs since March 2021.

Detectify 4 mentions
ContextForge.dev 2 mentions
  • What are the actual security implications of port forwarding?
    Detectify once made an offer of making free scans which I took them up on. There are plenty of free Content Security Policy (CSP) and other vulnerability checkers around such as Observatory or Pentest. Shields UP!! Will identify which... Source: about 3 years ago
  • Ask HN: Who is hiring? (February 2022)
    Detectify | Community Manager, Crowdsource | REMOTE (Offices in Boston, US & Stockholm, Sweden. We help with relocation if wanted) https://detectify.com/ We are a cyber security company in the industry, and more specifically the EASM... - Source: Hacker News / almost 5 years ago
  • DAST in Gitlab
    A concept-level idea would be this: 1) For your staging/UAT environment pipeline stages, add a "DAST scan" step, eg. With Detectify (which also has an API accommodating this need) 2) I'd assume, independently from the DAST scan, you... Source: over 5 years ago

View more

  • Shared Memory for Multiple AI Coding Agents (What They Already Share, and What They Don't)
    Init links the folder to a project, so every agent working in that repo reads and writes the same memory, and it adds the rules that make sessions check who else is live before big changes. For Cursor, Copilot, Claude Desktop and... - Source: dev.to / 16 days ago
  • Why AI Coding Agents Contradict Earlier Decisions (and How to Stop It)
    I built ContextForge because I was losing this argument with my own agents several times a week. The idea is small: when we decide something, the agent saves the decision with the reason, in the project's memory. The next session, in... - Source: dev.to / 30 days ago

Alternatives to Detectify and ContextForge.dev

When comparing Detectify and ContextForge.dev, you can also consider the following products.