"How to create and edit edge functions on Supabase" matching MCP servers:

Architectural Gatekeeper for AI coding. Prevents "tunnel vision" bugs by forcing the AI to verify dependencies (via AST parsing) before editing files. Supports JavaScript & TypeScript. Blocks unsafe edits until the AI proves it understands the impact

Enables Claude to use Google Gemini as a secondary AI through MCP for large-scale codebase analysis and complex reasoning tasks. Supports both Gemini Flash and Pro models with specialized functions for general queries and comprehensive code analysis.

A runtime-free MCP server that converts source code into AST🌲, regardless of language.

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

Enables automated migration of Vue projects to React with intelligent analysis, task management, and learning from user modifications.

Enables local, deterministic review of GitHub and GitLab pull request diffs for secret leaks, OWASP injection issues, WCAG 2.2 AA/EU EAA accessibility gaps, EU AI Act transparency, and database RLS risks, producing risk scores, merge decisions, committable suggestions, and SARIF exports.

Enables AI-powered GitHub interactions including repository analysis, code search, PR reviews, and more through the MCP protocol.

Enables AI assistants to analyze project folders for dependencies and frameworks and fetch current documentation or datasheets from the web.

Enables migration of test automation projects from WebDriverIO to Playwright using AST-based transformations. Provides tools for analyzing tests, converting syntax, refactoring to Page Object Model, and generating migration reports.

Lets AI coding agents read an outline of a large file or a digest of noisy command output instead of the full text, while every hidden line stays retrievable on disk through a run handle. Agents can request only the line ranges, slices, or grep matches they need and list recent runs, cutting token spend without losing information.

Converts vector PDF circuit schematics into evidence-preserving SchematicIR JSON with tools to inspect, convert, and validate schematic PDFs.

Enables AI agents to analyze and diff binaries by driving Ghidra headless or inside its GUI, exposing native reverse-engineering tools such as listing functions and segments, searching strings, decompiling, disassembling, and following cross-references. Ships with a devcontainer and supports local stdio or remote HTTP deployment.

Enables MCP clients such as Claude Desktop or Cursor to inspect a coffee-shop sales database schema, validate SQL, and run guarded read-only queries. It supports natural-language questions by exposing tools for schema description, SQL checking, and safe query execution.

Enables AI coding agents to extract Figma design data and convert it into Flutter widgets and screens. Supports theme setup, component analysis, asset exports, and provides Flutter implementation guidance from Figma designs.

Enables MCP clients to load eight on-demand coding skills and inspect project repositories through bounded, read-only map, search, read, diff, checks, and style tools. It keeps context lean by loading skill bodies only when needed and limiting repository scan and output sizes.

Twelve tools combine per-function complexity and branch coverage to rank work and check edited functions against their ceiling. Packets include source, uncovered lines, change-coupled files and near-duplicates. MCP calls can write local caches and metadata; they do not run test suites, edit source or claim work.

Call graph MCP server for Rust, Python, TypeScript, TSX, and JavaScript. Every caller and callee carries a resolution field showing how the reference was matched to a definition, plus multi-hop impact analysis for refactoring. Local-only, single binary, no network egress. Benchmarked against grep, ripgrep, and ctags on a 120-item hand-verified golden set, including the cases where it loses.

Navigate, search, and edit large codebases, logs, and data files that exceed AI context limits.

A field-level semantic change impact analysis MCP server for Claude Code, enabling natural language queries to find affected code when modifying fields, strings, or functions across multiple languages.

Cross-repository code intelligence server that enables AST-based search for functions, classes, types, and API routes across local JavaScript/TypeScript and PHP repositories.

A deterministic structural code map server for AI agents, giving them the shape of a codebase (imports, exports, classes, functions, signatures, comments, TODO-markers) without reading whole files into context. Powered by tree-sitter WASM grammars, it runs anywhere Node 18+ works.

Provides comprehensive Pine Script v6 documentation and tools to help AI assistants look up functions, validate syntax, and generate accurate code. It enables linting, version conversion from v5 to v6, and deep conceptual analysis to prevent code hallucinations.

Metatron is a self-hosted system that captures a codebase's real implementation decisions — preferred patterns, rejected approaches, edge cases, internal conventions — as structured priors, and serves them to coding agents over MCP

Enables AI coding assistants to scan projects for security issues such as leaked API keys, missing Supabase RLS, open Firebase rules, unauthenticated routes, and hallucinated packages, then fix and verify the results.

A ruthless, read-only code review MCP server that analyzes code produced by AI coding assistants, catching missing requirements, security vulnerabilities, edge cases, and performance issues without ever modifying files.

A robust, language-agnostic Model Context Protocol (MCP) server that provides AI coding agents with the ability to edit files surgically via Abstract Syntax Trees (AST) instead of relying on token-heavy, brittle search-and-replace or diff operations.

Provides the real exported API surface and type signatures of any npm package, extracted from its published TypeScript declarations, enabling AI coding agents to use functions accurately and avoid inventing nonexistent APIs.

Static security scanner for AI-generated (vibe-coded) Supabase and Next.js apps. Runs as an MCP server so an LLM can scan, explain findings, and produce fixes while it writes code, all locally and offline.

Assigns personality types to functions, rates variable name energy, and suggests aesthetic alternatives for code, providing an unscientific yet entertaining vibe assessment.

Enables read-only querying of a local repository through a deterministic tree-sitter symbol and edge graph, exposing keyword search with exact file:line hits, regex text search, per-file symbol skeletons, caller/callee traversal, and directory-level maps of clusters, hubs, and hotspots over stdio.