"Coder" matching MCP servers:

The most powerful open-source Cairo code generator.

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.

Enables Codex to delegate coding tasks to a locally hosted Qwen model through an MCP tool, which can read, write, patch, test, and inspect git diffs inside an allowed workspace.

Enables hands-free voice collaboration with a coding agent: you speak requirements aloud and hear only short, plain-language progress and completion summaries while the agent edits code, runs tests, and fixes bugs in the background. It also handles continuous speech recognition with automatic turn detection, barge-in interruption, and spoken approval prompts before risky operations.

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 AI agents to generate, compile, and fix Rust projects from natural language descriptions using LLMs and the Rust compiler.

Runs local coding CLIs (Claude Code / OpenAI Codex) asynchronously on Windows, enabling agents to spawn tasks, poll status, and retrieve results including git diffs, while preventing commits and pushes.

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.

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.

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.

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.

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.

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.