oraios/serena

* 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