CodeForces
LeetCode
Codechef
AlgoExpert.io
Project Euler
Interview Cake
interviewing.io
CodingInterview
ContextForge.dev
Agentmemory
OpenMemory MCP
ContextForge is persistent, searchable memory for AI coding agents โ 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 recalls it later with semantic search โ across sessions and across projects.
Works with: Claude Code, Claude Desktop, Cursor, GitHub Copilot, ChatGPT, and Windsurf.
CodeForces ContextForge.devContextForge.dev's answer:
ContextForge is memory that lives at the MCP layer, so it works across every AI coding agent at once โ Claude Code, Cursor, GitHub Copilot, ChatGPT, and Windsurf โ 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 โ 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 โ Claude Code, Cursor, GitHub Copilot, ChatGPT, Windsurf โ 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 โ 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.
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Your preparation should not be random. Platforms like LeetCode, Codeforces, and GeeksforGeeks are toolsโbut what matters is how you use them. - Source: dev.to / 3 months ago
Most people who do competitive programming have moved to: . - Source: Hacker News / 6 months ago
At first, the problems on platforms like Codeforces felt overwhelming. But after a few rounds, I realized something important:. - Source: dev.to / 10 months ago
Check it out and start competing today: https://codeforces.com/. - Source: dev.to / 10 months ago
The researchers created their dataset from CodeContests and public Codeforces solutions, enriched with metadata. For supervised fine-tuning, they structured the data as prompt-completion pairs, using problem statements as prompts and solutions as completions. The balanced dataset contained 1.2 million samples, each averaging 1,500 tokens. - Source: dev.to / over 1 year ago
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OpenMemory MCP - Your private, local memory layer for all AI tools
AlgoExpert.io - A better way to prep for tech interviews
Project Euler - Project Euler is a series of challenging mathematical/computer programming problems that will...