MCP Web Host

Hacker News

MCP Web Host

Hey folks! I just launched https://mcphost.link/ a web-based MCP host that lets you connect to multiple remote MCP servers and interact with them through a simple chat interface. Key Features Multi-server support: connect to several MCP servers at once OAuth 2.0 & Bearer Token auth (with PKCE) Persistent sessions: servers + credentials saved locally Full MCP features: tools, resources, prompts LLM support: bring your own inference backend The goal is to make exploring and working with the Model Context Protocol much more approachable. Happy to answer questions, take feedback, or hear feature requests!

Visit product View on Hacker NewsDec 29, 2025

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Actual performance

2points

1comments

Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, mcp, context · Missing: mac, agents, macos

92%92% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

AppSumoStrong fit for a featured deal · Strong signals: host, interface · Missing: plus, platform, intuitive

63%63% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal

56%56% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

54%54% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

41%41% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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