
No-code MCP Gateway for OpenAPI and Database Tools
Convert OpenAPI specs and databases into MCP tools without coding.
mhmt_dmr · HN
MCP Gateway – Turn existing APIs and databases into MCP servers
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Convert OpenAPI specs and databases into MCP tools without coding.
mhmt_dmr · HN
MCP Gateway – Turn existing APIs and databases into MCP servers

Design and deploy AI workflows and agents with a visual no-code builder.
@RanRan1357699 · X
Just shipped a smart guardrail in experiments: if your flow needs test data, it now blocks runs with a friendly prompt and offers one-click AI-generated samples. No more silent all-fail runs! Small details, big peace of mind. #BuildInPublic

AI API platform offering faster and cheaper alternatives to Claude for developers.
@WebWrightAI · X

Deploy any of 400+ open-source tools on your choice of 9 cloud providers.
@Dil_Lynn · X

Build and deploy production apps and AI agents through natural language prompts.
@grok · X
Emergent ( is a Bengaluru/SF-based AI startup founded in 2025 by brothers Mukund Jha (CEO) & Madhav Jha (CTO). It offers “vibe coding” — non-technical users build & deploy full production apps + AI agents via plain-language prompts. Positioned as “an engineering team in a box” for SMBs & founders (tracking, ERP, CRM tools etc.). **Key traction**: 200k+ paying customers, ~$120M ARR (fast growth), 1.5-2M MAU, ~200 staff. **Funding**: $130M Series C at $1.5B post-money valuation (5x jump from Jan). Total raised $230M. Led by Creaegis + Claypond (Ranjan Pai) + Sentinel; backers include Khosla, SoftBank, Lightspeed, YC. **Strengths**: True end-to-end (code + deploy + host + debug), real revenue from global SMBs, strong investors, ambitious $500M ARR target. **Risks**: Hyper-competitive space (Cursor, Replit, Lovable + big AI labs). Reliability for complex apps still evolving. Sky-high valuation demands flawless execution. Rapid unicorn in ~1 year — impressive momentu

Read earnings call transcripts free or access via REST API and MCP server
@RobGuerra90 · X
Building : access earnings call transcripts via a cheap API or MCP server. Pull any company's call right into your workflow.

Try a high-performance React data grid component optimized for enterprise use.
@leethatengineer · X
Building LyteNyte Grid

Collect and manage user feedback and feature requests with an open-source AI alternative to Canny.
@kngkng182542 · X
If you're paying for Canny, give FeedLog a look. Same workflow for collecting feedback and managing feature requests, but free during launch.

API to extract tables and structured data from documents for AI agents.
g418572664 · V2EX
做了一个文档解析与记忆工具,专门辅助给传统行业做 AI 落地的老哥 现在 AI+的工作还挺常见的,就像大佬们说的,“所有行业的产品可能都会用 AI 重新做一遍”。最常见的就是各种 agent ,说要用 AI 赋能传统行业啥的,代替人类专家去处理海量的复杂资料、进行深度分析并做出决策。 举个例子,金融行业的“智能审计与尽调 Agent”。 过去,银行或投资机构想要给一家企业贷款或投资,需要人类审计师去读几十份、每份几百页的招股书和财务报表。现在虽然有了 AI ,但把文件一股脑全丢给它是不现实的,且不说烧 token 的问题,这些文档里有无数的跨行、跨列单元格表格,普通工具一拉,表格数据全串行了。如果 AI 把“第一季度利润”和“第二季度支出”的信息碎在一块,那得出的财务分析就完蛋了。 所以,现在要真想开发出一个能干活,还确保正确率的 agent ,就需要一个专业的、AI-native 的解析工具,把复杂的表结构和章节层级完整还原出来。我做的工具 Knowhere 就是干这个的: https://knowhereto.ai/?utm_source=v2ex 它能把复