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Serena

by oraios

Adds symbol-aware code retrieval, editing, refactoring, and debugging to MCP-compatible coding agents.

Install Serena

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No confirmed install command yet

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Open setup steps on GitHub

Overview

oraios/serena MCP server gives coding agents IDE-like tools for navigating, editing, refactoring, and debugging code at the symbol level. It uses language servers by default, with an optional JetBrains plugin backend, and exposes these capabilities through MCP. Connect it by letting an MCP client launch Serena or by running it in HTTP mode and supplying its URL. It is a fit for agents working across large, multi-file codebases where semantic relationships matter.

Use cases

  • Navigate symbols and references across a large codebase
  • Refactor code across multiple files
  • Inspect declarations, implementations, and diagnostics
  • Query project structure through an MCP-compatible coding agent

Key features

  • Symbol-aware code retrieval and editing
  • Language-server backend for more than 40 languages
  • Optional JetBrains Plugin backend
  • Reference, declaration, implementation, and diagnostic lookup
  • Semantic refactoring and debugging support
  • Memory system for long-lived agent workflows

Security & health

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Adoption & maintenance

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GitHub stars30kStargazers on the source repository.
Last commitTodayMost recent push to the default branch.
Directory activity10 viewsConfig copies, upvotes, and views on AllMCPs.

How Serena works

What oraios/serena does

oraios/serena provides semantic code retrieval, editing, refactoring, and debugging capabilities for AI coding agents. Rather than treating a project as a collection of text ranges, its tools operate around symbols and the relationships between them. This lets an agent inspect code structure, locate references, and make changes with an IDE-style understanding of the project.

The server is designed for use with MCP-compatible clients and LLMs. Serena supplies the coding tools; the connected model remains responsible for deciding which tools to call and how to apply the results. Its focus is the 🤖 Coding Agents category, particularly workflows involving navigation and changes across multiple files.

How it works

Serena can use one of two analysis backends. The default option integrates language servers implementing the Language Server Protocol. These servers are generally open-source or freely available and provide language-specific information about symbols, declarations, implementations, references, and diagnostics.

A second option is the Serena JetBrains Plugin, which uses the analysis and editing facilities of a supported JetBrains IDE. The plugin is paid and offers a free trial. It supports the languages and frameworks handled by JetBrains IDEs; IntelliJ IDEA, PyCharm, Android Studio, WebStorm, PhpStorm, RubyMine, and GoLand are listed as supported environments, while Rider and CLion are unsupported.

The language-server backend covers more than 40 languages, including Python, Java, JavaScript, TypeScript, C#, C/C++, Go, Rust, Kotlin, Ruby, PHP, Swift, Scala, Dart, Elixir, Haskell, Lua, Terraform, YAML, JSON, HTML, CSS, SQL-adjacent project formats, and many others. Actual semantic coverage depends on the language server in use.

Setup and configuration

MCP clients can connect to Serena in either of two ways:

  • Give the client a launch command so it starts the MCP server when needed.
  • Start Serena yourself in HTTP mode and configure the client with the server URL.

Serena includes a multi-layer configuration system for adapting its broad tool set to different projects and agent workflows. The project also provides a REPL-based agent interface in Serena v2, alongside the MCP interface.

The connected client must support MCP. Examples named by the project include Claude Code, Codex, OpenCode, Gemini CLI, VS Code integrations, Cursor, JetBrains IDE integrations, Claude Desktop, Codex App, and OpenWebUI.

Tools and capabilities

The available capabilities include:

  • Finding symbols and declarations.
  • Producing a symbol overview or file outline.
  • Finding symbols that reference another symbol.
  • Finding implementations where the language server supports the operation.
  • Querying external projects.
  • Reading diagnostics and inspections.
  • Searching project dependencies through the JetBrains backend.
  • Inspecting type hierarchies through the JetBrains backend.
  • Editing and refactoring code using semantic structure rather than only line-based text operations.
  • Supporting long-lived agent workflows through a memory system.

Declaration lookup generally does not cover declarations in external dependencies when using language servers. Implementation lookup is also limited by the capabilities of the selected language server.

Limitations and notes

Serena does not replace the LLM or coding client: it exposes tools, while the model orchestrates the coding task. Backend choice affects available analysis features. The language-server route depends on suitable language-server support for the target language, while the JetBrains route requires a supported JetBrains environment and uses a paid plugin after its trial.

The project is licensed under GPL-3.0-or-later. It is intended for projects where symbol relationships and semantic navigation are useful; simple text edits and non-code tasks may not need its full tool set.

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Frequently Asked Questions about Serena

oraios/serena is an MCP server that connects AI coding agents to project code through language servers or a JetBrains plugin. Its main tools support symbol-aware code retrieval, editing, refactoring, debugging, references, declarations, implementations, diagnostics, and code-structure exploration across supported languages.

Configure your MCP client to launch Serena with its command, or run Serena in HTTP mode and provide the resulting URL. The project supports MCP clients including Claude Code, Codex, Gemini CLI, Cursor, VS Code integrations, JetBrains integrations, and Claude Desktop.

Yes, oraios/serena works with Cursor through MCP. Configure Cursor either to launch the server or to connect to a Serena instance running in HTTP mode.

The language-server backend supports more than 40 languages, including Python, Java, JavaScript, TypeScript, C#, C/C++, Go, Rust, Kotlin, Ruby, PHP, Swift, Scala, Dart, Elixir, Haskell, Lua, Terraform, YAML, JSON, HTML, CSS, and many others. Coverage depends on the language server.

Yes, oraios/serena can use its JetBrains Plugin as an alternative to language servers. The paid plugin has a free trial and works with supported JetBrains IDEs such as IntelliJ IDEA, PyCharm, Android Studio, WebStorm, PhpStorm, RubyMine, and GoLand.

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