"Exploring Supabase Features and Services" matching MCP servers:

Provides Dev Container Features that install code intelligence (LSP) and repository knowledge search (Orama) MCP servers into any dev container, enabling coding agents to perform go-to-definition, find references, and hybrid search over project files.

Enables AI agents to perform software engineering tasks inside an isolated, deterministic sandbox—exploring repositories, reproducing failures, applying patches, running tests, and verifying solutions against hidden suites through MCP tools.

Bug-report triage and fix-dispatch MCP for vibe coders. Ask your AI coding agent for a plain-English diagnosis of any user-reported bug — with evidence, blast radius, and a paste-ready fix prompt — then dispatch an automated GitHub fix PR without a second LLM key. 71 tools, Supabase-backed, MIT SDK. npx @mushi-mushi/mcp

A specialized toolchain that guides AI agents through a structured 'Atomic Development' workflow for building Python FastAPI and Supabase backends. It manages project scaffolding and enforces dependency-ordered generation of database models, API routes, and tests.

Enables AI-powered code editing and development tasks through natural language conversations with Claude, using Aider's capabilities for improving code, adding features, fixing bugs, refactoring, and checking status.

Bridges MCP clients to OpenCode's headless API, enabling AI to delegate autonomous coding tasks like building features, debugging, and refactoring across multiple projects.

Brings all SuperClaude features to Gemini CLI, enabling advanced coding assistance, persona switching, and token optimization.

Enables intelligent task management, multi-agent workflows, and cross-IDE project management through the BMAD methodology, with features like time tracking, quality gates, and project templates.

Enables AI coding agents to generate standardized code using scaffolding templates, enforce architectural patterns, and validate outputs programmatically. Supports creating projects from boilerplates and adding features to existing codebases while maintaining team conventions.

AI-native project management with persistent memory for coding agents. 17 MCP tools for features, stories, sprints, architecture decisions, knowledge base, and session tracking.

Enables AI coding assistants to drive spec-driven development through slash-command workflows for planning, exploring, implementing, updating, and finalizing changes, with local daemon and project registry support.

Enables AI coding assistants like Cursor and Claude to engage in real-time two-way dialogue, allowing them to pause for clarification and request user confirmation before executing tasks. It features a modern UI for managing interaction prompts, predefined options, and project analysis to reduce errors and API costs.

A coordination layer for coding agents that provides identities, message threading, and searchable history. It features file reservation leases to prevent agents from overwriting each other's work in multi-agent environments.

Enables AI harnesses to run iterative loops on code repositories with built-in quality evaluations, security gates, and approval workflows for tasks like fixing tests or implementing features.

Local-first MCP server that indexes all projects on your machine and provides coding agents with briefings about each project's stack, services, and run instructions, so they can start sessions with context across all repos. No cloud, no accounts, no telemetry.

Enables Claude Code sessions to wait for a durable, exact-head GitHub pull-request review and continue the same review/fix/push loop without polling, using Supabase durable state and Realtime wake-ups via ordinary stdio MCP.

A self-hosted remote MCP server that provides reusable prompts and development conventions across various AI tools. It features a modular architecture for organizing and namespacing custom prompts to streamline AI-assisted coding workflows.

An autonomous MCP server for AI-powered software generation using Gemini and Groq, with features like dual-engine strategy, visual inspection, and QA sentinel.

An autonomous AI development agent that enables full-stack coding, automated verification, RAG-powered code search, and quality assurance through MCP tools. Supports Gemini CLI, Claude Code CLI, with features like parallel verification, security scanning, and spec-driven development.

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