"Developer tools for a NextJS and FastAPI tech stack with Firebase and Vercel" matching MCP servers:

Visual tech-stack inventory of any codebase: languages, frameworks, databases, AI SDKs, infra.

Enables AI coding assistants to inspect FastAPI applications, routers, and Pydantic models, including generating TypeScript interfaces and Zod schemas and discovering backend routes without hallucination.

An MCP server that gives Claude Code IDE-level intelligence for FastAPI projects — semantic code navigation, safe renaming, route inspection, dependency trees, and Pydantic model analysis. Instead of Claude reading files blindly, it calls structured tools backed by Jedi (Python language server) and Python's AST.

Enables language models to explore and analyze source code repositories through read-only tools for listing directories, reading files, searching code, finding symbols, and inspecting git history, with strict sandboxing and security controls.

A token-efficient, codebase-aware AI agent runtime that provides MCP tools for starting runs, getting run states, explaining code, and finding files.

Provides MCP tools for GitHub code search, Jira sprint status, pull request risk analysis, and project metrics, enabling agentic workflows for developer productivity.

Enables coding agents to locate the right files and conventions in a Next.js project in a single call, drastically reducing token usage compared to searching.

An MCP server and standalone library that gives AI assistants superpowers for developing on Xano — complete with documentation, code validation, and workflow guides.

A Model Context Protocol server that helps programmers understand code by providing explanations, tech stack analysis, and best practice suggestions through prompt templates.

An MCP server that wraps OpenAI's Codex CLI to automate repository cloning and code analysis tasks. It enables users to execute complex coding requests on specific Git branches and subfolders using standardized MCP tools.

MCP server providing npm registry search, package details, dependency auditing, bundle size estimation, and package comparison tools for AI agents.

An MCP server that provides a persistent sandbox for AI coding agents to explore codebases server-side, returning only compact summaries to reduce context consumption.

Enables developers to analyze Odoo errors, inspect addons and manifests, statically validate XML views, Python models, and security files, run unified addon health checks, and verify live metadata through read-only XML-RPC.

A Python framework that exposes developer tools through MCP, REST API, and CLI from a single shared registry, enabling AI assistants, HTTP clients, and terminal users to access the same tools.

An MCP server that provides tools for React and TypeScript development, including generating typed form components, explaining TypeScript compiler errors, and producing Shadcn UI installation commands.

Provides AI-callable tools for modernizing legacy applications, including stack detection, API contract extraction, SQL to Flyway conversion, and migration effort estimation.

Exposes Language Server Protocol (LSP) tools such as diagnostics, goto definition, find references, symbols, and rename as a stdio MCP server.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Provides documentation generation and analysis tools for AI agents, including JSDoc generation, README analysis, changelog generation, API documentation, and code comment analysis.

Enables file reading with pagination and regex-based code search across a codebase using grep.

Local MCP servers that give Claude Code access to other tools mid-session.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

Architecture-index MCP tools for kernelee apps that combine static analysis and runtime wiring into a JSON index, enabling coding agents to query control flow and dependencies via the Model Context Protocol.

Enables Claude Code to use VS Code's tools, including diagnostics, symbol renaming, command execution, file opening, workspace listing, semantic search/API reference, terminal context, and integrated browser page interaction. It lets Claude see and act on the user's VS Code window, including shared browser pages and Markdown Editor selections.

Code linting and style checking tools for AI agents, exposed as an MCP server. Supports style checks, naming conventions, complexity analysis, dead code detection, and import analysis.

Enables querying a TypeScript codebase's graph for call flows, type relationships, and symbol locations without reading file bodies.

MCP server providing configuration file tools for AI agents. Parse, validate, merge, convert, and diff configuration files across all common formats.

A Model Context Protocol (MCP) server that provides TypeScript development tools for automated refactoring and code analysis.

Integrates Google's Gemini AI models into Claude Code and other MCP clients to provide second opinions, code comparisons, and token counting. It supports streaming responses and multi-turn conversations directly within your existing AI development workflow.

Enables AI agents to safely read, search, and inspect a local git repository, including PR-style diffs and changed-file summaries. It also supports opt-in allowlisted test runs.