GoHalves VS ContextForge.dev

GoHalves's answer

Most partnership tools help you manage relationships you already have. GoHalves creates them.

Three things together, and no competitor does all three. It matches B2B software brands to each other rather than to affiliates or resellers. Every member is vetted before entering the pool, so you are not matched with someone who signed up with a card and a landing page. And it does not stop at the introduction, it drafts the campaign for both sides from both profiles.

The rule underneath all of it is reciprocity. Every campaign type is a two-way exchange. If nothing flows both ways, it cannot be created on the platform.

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.

GoHalves's answer

Partner relationship management tools assume you already have partners. They administer programmes, track affiliates and pay commissions. The relationship they manage is asymmetric, one side promotes the other for money.

GoHalves is the step before that, and the relationship is symmetric. It finds you a company with an overlapping audience that is not competing with you, and both sides promote each other. No commission changes hands.

If you have a partnerships team and a signed roster, buy a PRM. If you have an audience and no partners, that is the problem GoHalves solves, at roughly a tenth of the price.

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.

GoHalves's answer

B2B software companies with an audience of their own and no partnerships team to work it.

Typically a founder or the marketing lead at a startup or scale-up, running a newsletter, a user base, a podcast or a social following, who wants reach without buying it. The practical floor is around a thousand subscribers, because below that there is nothing to trade.

Early access is starting with companies building in and around AI, and widening as the pool grows.

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.

GoHalves's answer

Every co-marketing partnership I have run started the same way. A spreadsheet, a fortnight of cold emails, and a decent chance the partner turned out to be a competitor.

The frustrating part was that the matches existed. Companies with the same audience and nothing to fight over are everywhere. They just have no way of finding each other, and no shared format for the trade once they do.

GoHalves is both halves of that. It finds the match, and it drafts the campaign.

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.

GoHalves's answer

The matching engine runs on vector embeddings rather than keyword tags. It scores audience overlap between companies, rules out anyone selling something too close to you, and weights for size parity so neither side is doing the other a favour.

Google and OpenAI models handle the language work, the in-app assistant that answers from your own account data, and the campaign assets drafted for both partners. Voice onboarding uses Deepgram Nova-3 through their EU endpoint, opted out of model training, with audio never persisted.

Built on TanStack Start and React 19 over Supabase Postgres.

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.