"Editing IDE Code Files in JetBrains" matching MCP servers:

Enables Codex to retrieve the currently selected file, line numbers, and code snippets from JetBrains IDEs. It leverages the official Claude Code plugin to provide real-time IDE context to the AI.

A proxy server that enables communication between clients (like Claude AI or VS Code) and JetBrains IDEs, allowing AI assistants to access IDE functionality.

Enables client-to-client communication between IDEs and development tools, allowing real-time collaboration across Cursor, VS Code, Windsurf, and other editors through bidirectional messaging and AI agent coordination.

An MCP relay that adds a use_jev tool to every connected server, letting the Jev model autonomously select and execute tool calls while the calling model supplies any required text values. It enables agents to delegate multi-step tool use across all configured MCP servers through a single unified interface.

Turns AI assistants into full-stack software engineers with 36 tools for cognitive reasoning, code validation, project scaffolding, and AI/IDE configuration generation across 130+ programming languages, databases, and frameworks.

Enables multi-agent council workflows for coding assistants, providing parallel independent reviews, plans, brainstorms, validation, and research with strict read-only boundaries.

An implementation of Claude Code as a Model Context Protocol server that enables using Claude's software engineering capabilities (code generation, editing, reviewing, and file operations) through the standardized MCP interface.

Give any LLM agent a real Android or iPhone. 62 MCP tools: tap, swipe, type, screenshot, screen-tree reading, app launch, camera, TTS, crash reports, batched execution. Android via ADB, iPhone via WebDriverAgent, on-device inference, Docker+KVM emulators. Works with Claude Code, Cursor, LangChain, LlamaIndex, and any MCP client. MIT.

Provides coding agents with typed classification, yes/no checks, scoring, ranking, and question-answering tools that return calibrated probabilities for fast, reliable decisions.

Enables Codex to offload expensive code reading, editing, and checking to a worker agent via Claude Code, supporting async jobs and long-running tasks.

Enables Claude Code to act as an autonomous Telegram agent with tools for replying, reacting, editing messages, searching history, and handling attachments. Includes a TUI watchdog for unattended operation.

This MCP server exposes Claude Code as a tool, allowing MCP clients to run Claude Code agents in specified working directories. It manages session persistence and returns structured results including summary, changed files, tests, and blockers.

Enables efficient AI agent operations through sandboxed Python code execution with progressive tool discovery, PII tokenization, and skills persistence, achieving up to 98.7% token reduction by processing data in a sandbox rather than in context.

Enables AI agents to write and execute Python code in an isolated sandbox that can orchestrate multiple MCP tool calls, reducing context window bloat and improving efficiency for complex workflows.

Enables Codex to delegate long-running work to Claude Code via blocking MCP calls, with tools for model discovery, run, and resume without polling.

This MCP server is designed for planning with Claude Code, Cline, or Cursor and making changes with Cerebras to maximize speed and intelligence while avoiding API limits. It uses the Qwen 3 Coder model for high-quality code generation and can be embedded in IDEs.

MCP server that lets you drive Claude Code sessions hands-free by voice from any MCP client, enabling remote models to send prompts, monitor progress, and get results read back.

Executes Python code in isolated rootless containers while proxying MCP server tools, reducing context overhead by 95%+ and enabling complex multi-tool workflows through sandboxed code execution.

Provides access to a library of 18 specialized skills, project templates, and prompt patterns for Claude Code. It enables automated workflows for feature development, security audits, and system maintenance through multi-agent collaboration.

A lightweight Model Context Protocol (MCP) orchestrator designed for efficiency at scale. It features TOON compression (reducing token usage by 30-90%) and Lazy Loading, making it the ideal solution for complex, multi-tool agentic workflows.