"Importing FastMCP from the mcp.server Python Module" matching MCP servers:

A personal MCP bridge that lets ChatGPT drive a local Codex CLI, translating instructions into Codex app-server threads and returning compact summaries of what Codex did.

Enables coding agents to execute Python code, run script files, and install pip packages locally via MCP.

Simple sequential thinking MCP in python

Production-ready MCP server starter templates in TypeScript and Python. Includes tool, resource, and prompt patterns with Claude Desktop integration configs.

Call OpenAI Codex from Claude Code for independent second opinions, structured code review, and delegated coding tasks through a FastMCP plugin that drives the codex CLI safely.

Prevents coding agents from repeatedly attempting the same failed fix by tracking attempts and blocking further fixes until the agent uses its own web search tool.

Enables MCP clients like VS Code and Copilot Chat to drive the Freebuff coding agent from the editor, with persisted sessions, transcripts, and a safe read-only ask agent by default.

Universal Python code execution MCP server that lets LLMs write and run Python for any task, with auto-install packages, streaming output, and automatic file display.

The IDE for agents — read by symbol, edit against a revision, validate with your own build, revert. It is a local stdio MCP server for coding agents. It reads code by symbol with tree-sitter and real language servers (Go, Java, Scala, TypeScript, Python, Rust, Ruby), edits against a known revision and returns compiler diagnostics with each edit, runs the repository's own build, test etc.

Enables AI agents to execute Python, TypeScript, and JavaScript code in persistent Jupyter kernels with stateful variables and imports across interactions.

Delegates work from MCP clients (like Claude Code) to the Codex CLI, allowing spawning of autonomous Codex subagents for tasks.

MCP server for the FloopFloop API that lets LLM hosts build, poll, and refine projects from natural language prompts.

MCP server for Python build123d to help AIs develop and reason about 3D models and CAD

Gives coding agents structural understanding of a codebase: it indexes Java and Python repositories to resolve symbols, call sites with confidence tiers, module dependencies, diff impact, and hotspots. It also ships an eval harness that measures whether this context actually helps an agent.

Exposes the active file and selection(s) from VS Code to MCP clients, enabling CLI coding agents to access current editor context.

A comprehensive MCP server providing tools for AI agents to interact with code, including reading symbols, importing modules, replacing text, and sending OS notifications.

A specialized server that provides advanced TypeScript code manipulation and analysis capabilities, enabling refactoring, navigation, diagnostics, and module analysis through Claude.

Enables delegating coding tasks to the official Antigravity CLI from any MCP client, with task listing, model selection, streamed event tracking, cancellation, and resumable sessions. Runs each task against an isolated copy of the repository so results can be previewed, tested, and only integrated into the original after explicit user confirmation.

An MCP server leveraging the Rust-based ty type checker to provide AI models with high-performance, semantic Python code analysis and structural navigation. It enables precise symbol searching, cross-file renaming, and diagnostic reporting to improve code understanding and editing accuracy.

Connects AI coding agents to Autodesk Fusion 360 for CAD automation, enabling natural language control over sketching, 3D modeling, and CAM operations. It uses a Python-based bridge and a custom add-in to execute over 80 tools ranging from simple geometry creation to complex assembly and parameter management.