"Self-Training Coder Resources and Tools" matching MCP servers:

MCP server that demonstrates the Resources feature by exposing static and dynamic resources, including contact data and personalized greetings, through MCP.

LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.

The most powerful open-source Cairo code generator.

An MCP server that enforces safe git commits by allowing only specified files and providing fixup capabilities for earlier commits.

Enables AI assistants to interact with Self, a self-awareness framework that connects daily actions to personal values, missions, and goals. Supports tracking foundations, intentions, projects, obstacles, and daily reflections through natural language.

Enables a primary coding agent to delegate bounded implementation and repair tasks to a local OpenAI-compatible model that edits a copy of the project, runs configured checks, and returns artifacts for review. Exposes stdio tools for capability discovery, task submission, progress polling, artifact reading, and cancellation.

Enables developers to integrate privacy-preserving identity verification from the Self protocol into their apps. Provides integration guides, code generation, blockchain configuration reading, and debugging assistance for age verification, airdrop eligibility, and humanity checks.

Integrates the Qwen3-Coder 30B parameter model with Claude Code through 5 specialized tools for code review, explanation, generation, bug fixing, and optimization. Optimized for 64GB RAM systems with advanced performance settings including flash attention and parallel processing.

An MCP server that supercharges AI assistants with powerful tools for software development, enabling research, planning, code generation, and project scaffolding through natural language interaction.

MCP server for Claude Code self-management, enabling hot restart and context compaction commands.

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.

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.

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.