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oraios/serena

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TLDR

Toolkit that gives AI coding agents IDE-level code understanding, semantic search, refactoring, and symbol navigation across 40+ languages via MCP.

Mindmap

mindmap
  root((repo))
    What it does
      Semantic code search
      Cross-codebase refactoring
      Symbol navigation
      IDE-grade tools for AI
    How it works
      MCP protocol
      LSP integration
      40+ languages
      JetBrains plugin
    Use cases
      Large project navigation
      Automated refactoring
      AI agent enhancement
      Code understanding
    Tech stack
      Python
      LSP
      MCP

Things people build with this

USE CASE 1

Give AI coding assistants like Claude Code or Cursor the ability to refactor functions across entire large codebases in one operation.

USE CASE 2

Find every place a method or function is called throughout a project without manual text searching.

USE CASE 3

Navigate between related symbols and understand code structure at the semantic level rather than raw text.

USE CASE 4

Improve AI agent effectiveness on complex projects by providing IDE-grade tools instead of basic search.

Tech stack

PythonLSPMCPJetBrains

Getting it running

Difficulty · moderate Time to first run · 30min

Requires Python environment setup and MCP server configuration to connect with IDE or agent.

Use freely for any purpose including commercial, as long as you keep the copyright notice.

In plain English

Serena is a toolkit that gives AI coding agents the kind of code-understanding capabilities normally found in professional IDEs (Integrated Development Environments). The problem it solves is that AI agents working with code typically rely on basic text search and line-number references, which become slow and error-prone in large codebases. Serena instead gives agents "semantic" tools, meaning they understand code at the level of symbols (functions, classes, variables) and their relationships, rather than just raw text. In practice this means an AI agent using Serena can do things like rename a function across an entire codebase in one step, find every place a method is called, or navigate between related symbols, operations that would otherwise require many careful steps with basic search tools. Serena works through MCP (Model Context Protocol), a standard that lets it plug into AI clients like Claude Code, GitHub Copilot, Cursor, and others. Under the hood it uses LSP (Language Server Protocol), the same technology code editors use to understand syntax, supporting over 40 programming languages. There is also a paid JetBrains IDE plugin for deeper integration. You would use Serena if you want your AI coding assistant to be significantly more effective on large or complex projects, by giving it real IDE-grade tools rather than text search. It is written in Python.

Copy-paste prompts

Prompt 1
How do I set up Serena with Claude Code to enable semantic code search and refactoring in my Python project?
Prompt 2
Show me how to use Serena's MCP integration to rename a function across my entire codebase automatically.
Prompt 3
What languages does Serena support via LSP, and how do I configure it for my tech stack?
Prompt 4
How can I use Serena to help my AI assistant understand symbol relationships and navigate a large monorepo?
Prompt 5
Walk me through installing the JetBrains Serena plugin and connecting it to my IDE.
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Generated 2026-05-18 · Model: sonnet-4-6 · Verify against the repo before relying on details.