Show HN: Real-time 4/20 cannabis sales dashboard using Estuary and Tinybird
(headset.io)
Real-time cannabis intelligence from the industry's most trusted data partner.
Real-time cannabis intelligence from the industry's most trusted data partner.
Show HN: AgentAPI – HTTP API for Claude Code, Goose, Aider, and Codex
(github.com/coder)
Control Claude Code, Goose, Aider, and Codex with an HTTP API.
Control Claude Code, Goose, Aider, and Codex with an HTTP API.
The Impact of MCP and LLMs on Software Development – A Practical Example
(wundergraph.com)
Model Context Protocol sounds fancy, but what can you actually do with it? In this post I'll show you how to use MCP to one shot real tasks like exploring an API schema, writing GraphQL queries, or configuring a router. There is no deep domain knowledge required, no hype, just practical examples.
Model Context Protocol sounds fancy, but what can you actually do with it? In this post I'll show you how to use MCP to one shot real tasks like exploring an API schema, writing GraphQL queries, or configuring a router. There is no deep domain knowledge required, no hype, just practical examples.
WordPress Feature API
(github.com/Automattic)
The WordPress Feature API is a system for exposing WordPress functionality in a standardized, discoverable way for both server and client-side use.
The WordPress Feature API is a system for exposing WordPress functionality in a standardized, discoverable way for both server and client-side use.
Meilisearch – search engine API bringing AI-powered hybrid search
(github.com/meilisearch)
⚡ A lightning-fast search engine that fits effortlessly into your apps, websites, and workflow 🔍
⚡ A lightning-fast search engine that fits effortlessly into your apps, websites, and workflow 🔍
Ask HN: Why don't we have a functional DSL for data+embedding+API pipelines?
(ycombinator.com)
I’ve been working on a pretty common problem: <p><pre> - I have structured data in JSONL files (in.jsonl, out.jsonl) - I match lines by a key - I transform them into (text, embedding) pairs - I optionally filter/map them - I batch them (into chunks of 50) - I push each batch into an external system (e.g. vector DB, Chroma) </pre> That’s it. Sounds trivial.
I’ve been working on a pretty common problem: <p><pre> - I have structured data in JSONL files (in.jsonl, out.jsonl) - I match lines by a key - I transform them into (text, embedding) pairs - I optionally filter/map them - I batch them (into chunks of 50) - I push each batch into an external system (e.g. vector DB, Chroma) </pre> That’s it. Sounds trivial.
Use the Gemini API with OpenAI Fallback in TypeScript
(sometechblog.com)
If you want to use Gemini’s public API, but at the same time have a safe fallback in case you have exhausted the rate limits, you can use the OpenAI TS/JS library and a few helper functions. In my particular case I needed a type-safe solution for a chartmaker app with a fallback since Gemini’s gemini-2.5-pro-exp-03-25 model is restricted to 20 request/min.
If you want to use Gemini’s public API, but at the same time have a safe fallback in case you have exhausted the rate limits, you can use the OpenAI TS/JS library and a few helper functions. In my particular case I needed a type-safe solution for a chartmaker app with a fallback since Gemini’s gemini-2.5-pro-exp-03-25 model is restricted to 20 request/min.
Show HN: Open Responses – Self-hosted OpenAI Responses API, works with any model
(github.com/julep-ai)
Open Responses lets you run a fully self-hosted version of OpenAI's Responses API. It works seamlessly with any large language model (LLM) provider—whether it's Claude, Qwen, Deepseek R1, Ollama, or others. It's a fully-compatible drop-in replacement for the official API. Swap out OpenAI without changing your existing Agents SDK code.
Open Responses lets you run a fully self-hosted version of OpenAI's Responses API. It works seamlessly with any large language model (LLM) provider—whether it's Claude, Qwen, Deepseek R1, Ollama, or others. It's a fully-compatible drop-in replacement for the official API. Swap out OpenAI without changing your existing Agents SDK code.
PayPal launches remote and local MCP servers
(paypal.com)
Model Context Protocol (MCP) supports managing and passing relevant information to models with appropriate context, so they operate properly within a given scope. Using this functionality, PayPal developed PayPal MCP Server to enable merchants to use natural language with their favorite MCP client to perform business tasks, such as creating or listing invoices.
Model Context Protocol (MCP) supports managing and passing relevant information to models with appropriate context, so they operate properly within a given scope. Using this functionality, PayPal developed PayPal MCP Server to enable merchants to use natural language with their favorite MCP client to perform business tasks, such as creating or listing invoices.
Prepare()-ing for execution: a new API for process creation
(github.com)
UNIX famously uses fork+exec to create processes, a simple API that is nevertheless quite tricky to use correctly and that comes with a bunch of problems.
UNIX famously uses fork+exec to create processes, a simple API that is nevertheless quite tricky to use correctly and that comes with a bunch of problems.
SignalBotOne – Notification Webhooks for Signal
(signalbot.one)
Receive messages on Signal via a simple API.Perfect for notifications and alerts.
Receive messages on Signal via a simple API.Perfect for notifications and alerts.
Show HN: Open Responses – Drop-In OpenAI Responses API Alternative for Any LLM
(ycombinator.com)
Hello HN! I just open-sourced Open Responses, a self-hosted implementation of OpenAI’s new Responses API that works with any LLM backend.
Hello HN! I just open-sourced Open Responses, a self-hosted implementation of OpenAI’s new Responses API that works with any LLM backend.
Why PostgreSQL needs a better API for alternative table engines?
(orioledb.com)
For a long time now, PostgreSQL has had an extensible Index Access Method API (called AM), which has stood the test of time and enabled numerous robust extensions to provide their own index types. For example: rum, pgvector, bloom, zombodb and others. PostgreSQL 12 introduced the Table AM API, promising equivalent flexibility for table access methods.
For a long time now, PostgreSQL has had an extensible Index Access Method API (called AM), which has stood the test of time and enabled numerous robust extensions to provide their own index types. For example: rum, pgvector, bloom, zombodb and others. PostgreSQL 12 introduced the Table AM API, promising equivalent flexibility for table access methods.
Show HN: FastOpenAPI – automated docs for many Python frameworks
(github.com/mr-fatalyst)
FastOpenAPI is a library for generating and integrating OpenAPI schemas using Pydantic v2 and various frameworks (Falcon, Flask, Sanic, Starlette, Tornado).
FastOpenAPI is a library for generating and integrating OpenAPI schemas using Pydantic v2 and various frameworks (Falcon, Flask, Sanic, Starlette, Tornado).
HTTPS-only for Cloudflare APIs: shutting the door on cleartext traffic
(cloudflare.com)
Today we’re announcing that we’re closing all of the HTTP ports on api.cloudflare.com.
Today we’re announcing that we’re closing all of the HTTP ports on api.cloudflare.com.
OmniAI: A unified Ruby API for integrating with AI providers
(github.com/ksylvest)
OmniAI provides a unified Ruby API for integrating with multiple AI providers, including Anthropic, DeepSeek, Google, Mistral, and OpenAI. It streamlines AI development by offering a consistent interface for features such as chat, text-to-speech, speech-to-text, and embeddings—ensuring seamless interoperability across platforms. Switching between providers is effortless, making any integration more flexible and reliable.
OmniAI provides a unified Ruby API for integrating with multiple AI providers, including Anthropic, DeepSeek, Google, Mistral, and OpenAI. It streamlines AI development by offering a consistent interface for features such as chat, text-to-speech, speech-to-text, and embeddings—ensuring seamless interoperability across platforms. Switching between providers is effortless, making any integration more flexible and reliable.
YouTube-transcript-API 1.0.0 released
(github.com/jdepoix)
Overhaul of the public API to move away from the static methods get_transcript, get_transcripts and list_transcripts
Overhaul of the public API to move away from the static methods get_transcript, get_transcripts and list_transcripts
Bundling MCP Servers in Every OpenAPI –> TypeScript SDK
(speakeasy.com)
It’s no longer enough for businesses to make their services available to developers. A great development experience also hinges on the ability for AI to access and integrate with available APIs. That’s why starting today, every TypeScript SDK generated by Speakeasy now bundles a runnable Model Context Protocol (MCP) (opens in a new tab) server enabling you to expose your API to the growing landscape of AI agents.
It’s no longer enough for businesses to make their services available to developers. A great development experience also hinges on the ability for AI to access and integrate with available APIs. That’s why starting today, every TypeScript SDK generated by Speakeasy now bundles a runnable Model Context Protocol (MCP) (opens in a new tab) server enabling you to expose your API to the growing landscape of AI agents.
Show HN: A Comprehensive, Compatible Open Source Alternative to Python Requests
(readthedocs.io)
Niquests is an elegant and simple HTTP library for Python, built for human beings. It is designed to be a drop-in replacement for Requests that is no longer under feature freeze.
Niquests is an elegant and simple HTTP library for Python, built for human beings. It is designed to be a drop-in replacement for Requests that is no longer under feature freeze.
MCP vs. API Explained
(norahsakal.com)
MCP (Model Context Protocol) is a new open protocol designed to standardize how applications provide context to Large Language Models (LLMs).
MCP (Model Context Protocol) is a new open protocol designed to standardize how applications provide context to Large Language Models (LLMs).
Great software design looks underwhelming
(seangoedecke.com)
Years ago I spent a lot of time reviewing coding challenges. The challenge itself was very straightforward - building a CLI tool that hit an API and allowed the user to page through and inspect the data. We allowed any language, so I saw all kinds of approaches1. At one point I came across a challenge I thought was literally perfect.
Years ago I spent a lot of time reviewing coding challenges. The challenge itself was very straightforward - building a CLI tool that hit an API and allowed the user to page through and inspect the data. We allowed any language, so I saw all kinds of approaches1. At one point I came across a challenge I thought was literally perfect.
Show HN: Agents.json – OpenAPI Specification for LLMs
(github.com/wild-card-ai)
The agents.json Specification is an open specification that formally describes contracts for API and agent interactions, built on top of the OpenAPI standard.
The agents.json Specification is an open specification that formally describes contracts for API and agent interactions, built on top of the OpenAPI standard.
Show HN: Superglue – open source API connector that writes its own code
(github.com/superglue-ai)
superglue allows you to connect to any API/data source and get the data you want in the format you need. It’s an open source proxy server which sits between you and your target APIs. Thus, you can easily deploy it into your own infra.
superglue allows you to connect to any API/data source and get the data you want in the format you need. It’s an open source proxy server which sits between you and your target APIs. Thus, you can easily deploy it into your own infra.
Show HN: A lightweight LLM proxy to get structured results from most LLMs
(l1m.io)
l1m is the easiest way to get structured data from unstructured text or images using LLMs. No prompt engineering, no chat history, just a simple API to extract structured json from text or images.
l1m is the easiest way to get structured data from unstructured text or images using LLMs. No prompt engineering, no chat history, just a simple API to extract structured json from text or images.
Awesome DeepSeek Integrations
(github.com/deepseek-ai)
Integrate the DeepSeek API into popular softwares. Access DeepSeek Open Platform to get an API key.
Integrate the DeepSeek API into popular softwares. Access DeepSeek Open Platform to get an API key.