
Capture2text
ABBYY Screenshot Reader
dpScreenOCR
Textify
KanjiTomo
Easy Screen OCR
Q-Dir
Instantly extract any text from your Mac's screen

Agentmemory
Mem0
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.

Which is more popular?
Based on our record, TextSniper seems to be a lot more popular than ContextForge.dev. While we know about 35 links to TextSniper, we've tracked only 2 mentions of ContextForge.dev.
Website, pricing, platforms and company facts side by side.
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| Website | textsniper.app | contextforge.dev |
| Pricing | ||
| Platforms | ||
| Company | 2020 | Startup from the United States · 2026 |
| Listed in |
In their own words, as submitted to SaaSHub.


TextSniper is an easy-to-use desktop Mac OCR app that can extract and recognize any non-searchable and non-editable text on your Mac's screen. As an extra feature, it can turn OCR text into speech. It is a super convenient alternative to complicated optical character recognition tools. The...
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...
What each product offers, as listed by its team.


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


Overall verdict
Why this product is good
Recommended for
Overall verdict
Why this product is good
Recommended for
Walkthroughs and reviews on video.
TextSniper Quick Demo
How to Make Claude Run Automated Workflows (ContextForge Skills Tutorial)
More videos
How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing TextSniper and ContextForge.dev.
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.
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.
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.
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.
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.
Share your experience with using TextSniper and ContextForge.dev. For example, how are they different and which one is better?
Recommendations tracked on public social media and blogs since March 2021.


Continuing working on my project - TextSniper https://textsniper.app/ macOS application for text recognition. - Source: Hacker News / about 2 years ago
I am still working on https://textsniper.app. - Source: Hacker News / about 2 years ago
For OCR of any PDF (or frozen hard-to-read jpg), I use the $12 forever TextSniper (https://textsniper.app). Source: over 3 years ago
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 / 17 days ago
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 / about 1 month ago
When comparing TextSniper and ContextForge.dev, you can also consider the following products.

Capture2Text enables users to quickly OCR a portion of the screen using a keyboard shortcut.
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Persistent memory for Claude Code, Codex & coding agents
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ABBYY Screenshot Reader turns text within any image captured from your screen into an editable format without retyping
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Your private, local memory layer for all AI tools
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Program to recognize text on screen
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A small tool which allows to copy text from dialogs and controls which don’t allow it otherwise.
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