Fly.io provides a secure and fast platform for deploying AI workflows and LLM-generated code using ephemeral, kernel-isolated virtual machines (Fly Machines). It offers features like secure sandboxing, fast startup times, a clean slate for each run, a simple API, and support for whole applications, not just code snippets.
Interact with opencode server over HTTP. The `opencode serve` command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.
An overview of popular techniques to confine LLMs' output to a predefined schema, covering API providers, prompting/reprompting strategies, and constrained decoding.
This document details the features, best practices, and migration guidance for GPT-5, OpenAI's most intelligent model. It covers new API features like minimal reasoning effort, verbosity control, custom tools, and allowed tools, along with prompting guidance and migration strategies from older models and APIs.
This article discusses how GitHub Models provides a free, OpenAI-compatible inference API to make AI-powered open source software more accessible. It details the challenges of AI inference (cost, local resources, distribution) and how GitHub Models addresses them, including setup, CI/CD integration, and scaling.
The Universal Tool Calling Protocol (UTCP) is an open standard that describes how to call existing tools directly, eliminating the need for wrappers. It focuses on direct communication with tool endpoints (HTTP, gRPC, WebSocket, CLI, etc.) to reduce latency and maintain existing security and billing systems.
This article lists and ranks the top Model Context Protocol (MCP) servers on GitHub as of June 2025, highlighting their capabilities and emphasizing the importance of security when granting agents access to sensitive data. It positions Pomerium as a solution for enforcing policy and securing agentic access to MCP servers.
|**GitHub Repository** |**Description** |
|---------------------------------|-----------------------------------------------------------------------------|
| github/github-mcp-server | Manages GitHub issues, pull requests, discussions with identity & permissions. |
| microsoft/playwright-mcp | Triggers browser automation tasks (QA, scraping, testing). |
| awslabs/mcp | Exposes AWS documentation, billing data, and service metadata. |
| hashicorp/terraform-mcp-server | Secure access to Terraform providers and modules. |
| dbt-labs/dbt-mcp | Exposes dbt’s semantic layer and CLI commands. |
| getsentry/sentry-mcp | Access to Sentry error tracking and performance telemetry. |
| mongodb-js/mongodb-mcp-server | Interacts with MongoDB and Atlas instances securely. |
| StarRocks/mcp-server-starrocks | Brings MCP to the StarRocks SQL engine. |
| vantage-sh/vantage-mcp-server |Focuses on cloud cost visibility. |
|**GitHub Repository** |**Description** |
|---------------------------------|-----------------------------------------------------------------------------|
| github/github-mcp-server | Manages GitHub issues, pull requests, discussions with identity & permissions. |
| microsoft/playwright-mcp | Triggers browser automation tasks (QA, scraping, testing). |
| awslabs/mcp | Exposes AWS documentation, billing data, and service metadata. |
| hashicorp/terraform-mcp-server | Secure access to Terraform providers and modules. |
| dbt-labs/dbt-mcp | Exposes dbt’s semantic layer and CLI commands. |
| getsentry/sentry-mcp | Access to Sentry error tracking and performance telemetry. |
| mongodb-js/mongodb-mcp-server | Interacts with MongoDB and Atlas instances securely. |
| StarRocks/mcp-server-starrocks | Brings MCP to the StarRocks SQL engine. |
| vantage-sh/vantage-mcp-server |Focuses on cloud cost visibility. |
This guide highlights 10 open-source MCP (Model Context Protocol) servers to boost productivity in Cursor, covering tools for API work, web scraping, design integration, and document conversion.
| **Server Name** | **Primary Function** | **Key Features** |
|---|---|---|
| Apidog MCP Server | API Development | Syncs with API docs, natural language queries, local caching. |
| Browserbase MCP Server | Web Interaction & Automation | Cloud browser sessions, screenshots, JavaScript execution. |
| Magic MCP Server | Generative AI | Placeholder images, text transformation, code generation. |
| Opik MCP Server | Real-time Web Search | Web search integration, content summarization, source citations. |
| Figma Context MCP Server | Design-to-Code | Access Figma data, convert designs to code, analyze UI elements. |
| Pandoc MCP Server | Document Conversion | Converts between Markdown, PDF, HTML, DOCX, etc. |
| Excel MCP Server | Excel Data Access | Read/write Excel data, generate visualizations, automate reporting. |
| Mindmap MCP Server | Mindmap Integration | Import/interpret mindmaps, convert to outlines, collaborative planning. |
| Markdownify MCP Server | Content to Markdown | Converts HTML to Markdown, cleans documentation. |
| Tavily MCP Server | Curated Knowledge | High-quality knowledge retrieval, AI-friendly summaries, multi-source aggregation. |
| **Server Name** | **Primary Function** | **Key Features** |
|---|---|---|
| Apidog MCP Server | API Development | Syncs with API docs, natural language queries, local caching. |
| Browserbase MCP Server | Web Interaction & Automation | Cloud browser sessions, screenshots, JavaScript execution. |
| Magic MCP Server | Generative AI | Placeholder images, text transformation, code generation. |
| Opik MCP Server | Real-time Web Search | Web search integration, content summarization, source citations. |
| Figma Context MCP Server | Design-to-Code | Access Figma data, convert designs to code, analyze UI elements. |
| Pandoc MCP Server | Document Conversion | Converts between Markdown, PDF, HTML, DOCX, etc. |
| Excel MCP Server | Excel Data Access | Read/write Excel data, generate visualizations, automate reporting. |
| Mindmap MCP Server | Mindmap Integration | Import/interpret mindmaps, convert to outlines, collaborative planning. |
| Markdownify MCP Server | Content to Markdown | Converts HTML to Markdown, cleans documentation. |
| Tavily MCP Server | Curated Knowledge | High-quality knowledge retrieval, AI-friendly summaries, multi-source aggregation. |
Running GenAI models is easy. Scaling them to thousands of users, not so much. This guide details avenues for scaling AI workloads from proofs of concept to production-ready deployments, covering API integration, on-prem deployment considerations, hardware requirements, and tools like vLLM and Nvidia NIMs.
This tutorial details how to use FastAPI-MCP to convert a FastAPI endpoint (fetching US National Park alerts) into an MCP-compatible server. It covers environment setup, app creation, testing, and MCP server implementation with Cursor IDE.
