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serena

A powerful MCP toolkit for coding, providing semantic retrieval and editing capabilities - the IDE for your agent

  • 30.6k stars
  • 2.1k forks
  • 114 open issues
  • Language: Python
  • License: NOASSERTION
  • updated

Install

local · uvx (python)
Claude Code CLI
claude mcp add serena -- uvx serena
  1. Run the command above in your terminal (Claude Code), or paste the JSON config into claude_desktop_config.json (Claude Desktop).
  2. Replace any <placeholder> values with your API keys or paths.
  3. Restart Claude. The MCP server and its tools appear automatically.

Package name inferred from the repository name. Verify it exists on PyPI, or clone https://github.com/oraios/serena and follow its README.

Editor's note

Serena is a Python-based MCP server that gives AI coding agents IDE-level capabilities by operating on code at the symbol level rather than relying on line numbers or text search. Its tools cover semantic code retrieval, cross-file renaming, refactoring, reference lookups, and debugging, all built on either Language Server Protocol (LSP) backends or an optional paid JetBrains plugin for deeper analysis. The server connects via MCP to a wide range of clients including Claude Code, Claude Desktop, Codex CLI, Cursor, VS Code, and JetBrains IDEs. During evaluation on a large Python codebase, Claude Opus described cross-file renames and reference lookups that would otherwise require eight to twelve manual steps collapsing into a single atomic call. Developers working on large or multi-language codebases stand to benefit most, as the symbol-aware approach reduces errors during complex refactors that naive text-based tools handle poorly.

README

MCP Servers overview

Full README on GitHub

The IDE for Your Coding Agent

  • Serena provides essential semantic code retrieval, editing, refactoring and debugging tools that are akin to an IDE's capabilities, operating at the symbol level and exploiting relational structure.

  • It integrates with any client/LLM via the model context protocol (MCP).

Serena's agent-first tool design involves robust high-level abstractions, distinguishing it from approaches that rely on low-level concepts like line numbers or primitive search patterns.

Practically, this means that your agent operates faster, more efficiently and more reliably, especially in larger and more complex codebases.

Tip

Serena v2 with the new REPL-based agent interface has been released.
Learn more about the new interface and how to configure it.

Video

What Our "End Users" Say

While it is humans who download and set up Serena, our end users are essentially AI agents. As the ones actually applying Serena's tools, they are in the best position to evaluate Serena.

We crafted an unbiased evaluation prompt that leads the agent to perform ~20 routine coding tasks, representative of everyday development work, in order to estimate the value added by Serena's tools when used alongside its own built-ins.

Here's a one-sentence summary of what the agents had to say:

Opus 4.6 (high) in Claude Code on a large Python codebase:

"Serena's IDE-backed semantic tools are the single most impactful addition to my toolkit – cross-file renames, moves, and reference lookups that would cost me 8–12 careful, error-prone steps collapse into one atomic call, and I would absolutely ask any developer I work with to set them up."

GPT 5.4 (high) in Codex CLI on a Java codebase:

"As a coding AI agent, I would ask my owner to add Serena because it gives me the missing IDE-level understanding of symbols, references, and refactorings, turning fragile text surgery into calmer, faster, more confident code changes where semantics matter."

GPT 5.4 (medium) in Copilot CLI on a large, multi-language monorepo:

"As a coding agent, I’d absolutely ask my owner to add Serena because it makes me noticeably sharper and calmer on real code – especially symbol-aware navigation, cross-file refactors, and monorepo dependency jumps – while I still lean on built-ins for tiny text edits and non-code work."

Different agents in different settings independently converge on the same verdict.

Give your agent the tools it has been asking for and add Serena MCP to your client!

See our documentation for the full methodology and much more detailed evaluation results, or run your own evaluation on a project of your choice.

How Serena Works

Serena provides the necessary tools for coding workflows, but an LLM is required to do the actual work, orchestrating tool use.

Serena can extend the functionality of your existing AI client via the model context protocol (MCP). Most modern AI chat clients directly support MCP, including

  • terminal-based clients like Claude Code, Codex, OpenCode, or Gemini-CLI,

  • IDEs and IDE assistant plugins for VSCode, Cursor and JetBrains IDEs (Copilot, Junie, JetBrains AI Assistant, etc.),

  • desktop and web clients like Claude Desktop, Codex App, or OpenWebUI.

:tv: See also: Introduction to Serena in 5 Minutes (YouTube)

To connect the Serena MCP server to your client, you either

  • provide the client with a launch command that allows it to start the MCP server, or

  • start the Serena MCP server yourself in HTTP mode and provide the client with the URL.

See the Quick Start section below for information on how to get started.

Programming Language Support & Semantic Analysis Capabilities

Serena provides a set of versatile code querying and editing functionalities based on symbolic understanding of the code. Equipped with these capabilities, your agent discovers and edits code just like a seasoned developer making use of an IDE's capabilities would. Serena can efficiently find the right context and do the right thing even in very large and complex projects!

There are two alternative technologies powering these capabilities:

  • Language servers implementing the language server protocol (LSP) — the free/open-source alternative which is used by default.

  • The Serena JetBrains Plugin, which leverages the powerful code analysis and editing capabilities of your JetBrains IDE (paid plugin; free trial available).

You can choose either of these backends depending on your preferences and requirements.

Language Servers

Serena incorporates a powerful abstraction layer for the integration of language servers that implement the language server protocol (LSP). The underlying language servers are typically open-source projects or at least freely available for use.

When using Serena's language server backend, we provide support for over 40 programming languages, including Ada / SPARK, AL, Angular, Ansible, Astro, Bash, BSL, C#, C/C++, Clojure, Crystal, CUE, Dart, Deno, Elixir, Elm, Erlang, Fortran, F#, GDScript, Gleam, GLSL, Go, Groovy, Haskell, Haxe, HLSL, HTML, Java, JavaScript, JSON, Julia, Kotlin, LaTeX, Lean 4, Lua, Luau, Markdown, MATLAB, mSL, Nextflow, Nix, OCaml, Pascal, Perl, PHP, PowerShell, Python, QML, R, Rego, Ruby, Rust, Scala, SCSS / Sass / CSS, Solidity, Svelte, Swift, SystemVerilog, Terraform, TOML, TypeScript, VB.NET, Vue, WGSL, Wolfram Language, YAML, and Zig.

The Serena JetBrains Plugin

The paid Serena JetBrains Plugin (free trial available) leverages the powerful code analysis capabilities of your JetBrains IDE. The plugin naturally supports all programming languages and frameworks that are supported by JetBrains IDEs, including IntelliJ IDEA, PyCharm, Android Studio, WebStorm, PhpStorm, RubyMine, GoLand, and potentially others (Rider and CLion are unsupported though).

See our documentation page for further details and instructions on how to apply the plugin.

Features

Serena provides a wide range of tools for efficient code retrieval, editing and refactoring, as well as a memory system for long-lived agent workflows.

Given its large scope, Serena adapts to your needs by offering a multi-layered configuration system.

Details

Retrieval

Serena's retrieval tools allow agents to explore codebases at the symbol level, understanding structure and relationships without reading entire files.

CapabilityLanguage ServersJetBrains Plugin
find symbolyesyes
symbol overview (file outline)yesyes
find referencing symbolsyesyes
search in project dependencies--yes
type hierarchy--yes
find declarationyes*yes
find implementationsyes**yes
query external projectsyesyes
diagnostics/inspectionsyesyes

: Will generally not work for declarations in external dependencies. *: Only available for some languages, limited by the language server functionality.

Refactoring

Without precise refactoring tools, agents are forced to resort to unreliable and expensive search and replace operations.

CapabilityLanguage ServersJetBrains Plugin
renameyes (only symbols)yes (symbols, files, directories)
move (symbol, file, directory)--yes
inline--yes
propagate deletions (remove unused code)--yes

Symbolic Editing

Serena's symbolic editing tools are less error-prone and much more token-efficient than typical alternatives.

CapabilityLanguage ServersJetBrains Plugin
replace symbol bodyyesyes
Topics
agentaiai-codingclaudeclaude-codecodexidejetbrainslanguage-servermcp-serverprogrammingvibe-coding
Frequently asked

What people ask about serena

What is oraios/serena?

oraios/serena is mcp servers for the Claude AI ecosystem. A powerful MCP toolkit for coding, providing semantic retrieval and editing capabilities - the IDE for your agent It has 30.6k GitHub stars and its last recorded update is dated 2026-10-20.

How do I install serena?

You can install serena by cloning the repository (https://github.com/oraios/serena) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.

Is oraios/serena safe to use?

Our security agent has analyzed oraios/serena and assigned a Trust Score of 95/100 (tier: Verified). See the full breakdown of passed checks and flags on this page.

Who maintains oraios/serena?

oraios/serena is maintained by oraios. The last recorded GitHub activity is dated 2026-10-20, with 114 open issues.

Are there alternatives to serena?

Yes. On ClaudeWave you can browse similar mcp servers at /categories/mcp, sorted by popularity or recent activity.

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