"AI Agent Coder with Awareness of Various SDKs" matching MCP servers:

A static-analysis knowledge base for TypeScript/NestJS codebases, served to AI agents over MCP for understanding code without hallucination and excessive token usage.

Loads entire codebase into LLM context for AI-assisted code understanding and editing.

Enables AI assistants to perform software-development tasks such as deep research, codebase mapping, context curation, requirements and user-story generation, full-stack starter project scaffolding, and multi-step workflow execution.

Enables AI assistants to research, plan and manage tasks, generate requirements and user stories, scaffold projects, analyze codebases, curate context, and run multi-step development workflows.

Enables AI assistants to research, plan, generate requirements, user stories, task lists, and full-stack starter projects, analyze codebases, curate context, and run multi-step software development workflows through MCP tools.

Enables AI assistants to conduct research, plan projects, generate PRDs, user stories and task lists, scaffold full-stack starter kits, map codebases, curate context, and execute multi-step development workflows.

Exposes read-only tools for OPC UA PLC tag monitoring and diagnostics, and enables template-driven, validated IEC 61131-3 SCL code generation with a mandatory human review gate before download.

Enables AI assistants and MCP-compatible clients to research, plan, generate requirements, analyze codebases, manage tasks, create user stories, and scaffold full-stack starter projects through specialized development tools.

Equips AI assistants and MCP clients with software development tools for deep research, codebase mapping, context curation, and multi-step workflow execution. It also generates product requirements documents, user stories, task lists, and fullstack starter projects.

Equips MCP-compatible AI assistants with tools for deep research, requirements and PRD generation, codebase mapping, context curation, task management, and fullstack starter-project scaffolding. It supports CLI, REPL, and server modes so developers can drive software development workflows through natural-language commands.

Enables AI assistants to research, plan, generate requirements and user stories, scaffold starter projects, map codebases, manage tasks, curate context, and run multi-step software-development workflows through MCP-compatible clients.

A TypeScript ESM MCP server exposing 20 public instruction tools and 7 utility tools, backed by 102 internal skills across 18 domain families — from requirements discovery and code quality through governance, resilience, and physics-inspired analysis.

Enables AI assistants to research topics, analyze codebases, generate requirements and user stories, scaffold starter projects, and run multi-step development workflows through natural language.

Enables AI assistants to conduct deep research, map codebases, curate context, generate requirements/user stories/task lists, scaffold full-stack starters, and execute multi-step workflows.

Enables AI assistants to research topics, map and analyze codebases across 35+ languages, curate context, and generate requirements documents, user stories, task lists, and full-stack starter projects. It also supports multi-step workflow execution and AI-native task management through a CLI, interactive REPL, or MCP client integration.

Extends AI assistants with software development capabilities such as deep research, codebase analysis, requirements and user-story generation, project scaffolding, context curation, task management, and multi-step workflow execution.

Enables AI assistants to perform software development tasks such as codebase analysis, research, planning, requirements and user-story generation, task management, project scaffolding, and multi-step workflow execution. It integrates with MCP-compatible clients like Claude Desktop, Cursor, and Cline AI.

Enables AI assistants to research, plan, generate requirements, map codebases, curate context, manage tasks, scaffold projects, and run multi-step software development workflows.

Enables AI assistants to research topics, plan software, generate requirements, create starter projects, map codebases, curate context, manage tasks, and run multi-step development workflows through MCP-compatible clients.

Enables AI assistants to research topics, map and analyze codebases, curate context, and generate PRDs, user stories, task lists, and fullstack starter projects through natural language commands or an interactive CLI/REPL. It also provides AI-native task management and multi-step workflow execution.