"Coder" matching MCP servers:

Provides Flutter and Dart reference data, code generation, live API lookups, and a verified sample corpus for AI coding assistants, enabling efficient Flutter development with accurate guidance and boilerplate generation.

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.

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

A self-hosted MCP server that gives ChatGPT full local machine access for coding tasks, including file editing, shell commands, git operations, and project exploration via 40+ MCP tools.

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

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

Enables MCP clients to securely execute bounded coding tasks through registered backends, with idempotent job submission, status polling, and artifact retrieval. It isolates each job in Git worktrees and supports optional branch publishing and pull request creation under strict policy constraints.

Bridges Claude with a local Ollama coding model, letting Claude delegate bounded implementation tasks to the local model while retaining reasoning, review, and safety enforcement.

Turns ChatGPT web into a local coding agent, enabling file edits, shell commands, Git operations, patches, and process management through 40+ MCP tools.

An MCP+HTTP control plane for routing work to multiple coding-agent CLIs through a normalized contract, enabling multi-agent coding pipelines with planning, implementation, review, and revision.

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 research topics, generate product requirements and user stories, map codebases, curate context, scaffold full-stack starter projects, and run multi-step development workflows.