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Serena

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The IDE for your coding agent with semantic retrieval and editing.

MCP ServerAI & KnowledgeLocal (stdio) 25.4k
View on GitHub
Updated 2026-06-15

What is the Serena MCP server?

Serena leverages language servers or the JetBrains plugin to provide relational understanding of code symbols, references, and dependencies. This enables agents to perform complex operations like cross-file renames and moves in a single atomic call, improving reliability on large projects.

Designed specifically for agent-first workflows, Serena abstracts away low-level details so LLMs can focus on high-level tasks. It works alongside existing client tools and supports multiple languages through LSP or proprietary analysis.

Install & connect

Set up this server, then add it to your MCP client.

Full setup instructions are in the GitHub repository.

Example prompts

Once connected, try asking your AI client:

“Use Serena to find all references to this function and suggest a safe rename.
“Perform a cross-file refactor to move this class into a new package.
“Show me the call graph for this method using semantic analysis.
“Help debug this error by locating related symbols and recent changes.

Security & permissions

Runs locally via stdio and requires read/write access to the user's codebase files. No remote API keys or external services are needed.

What you can do with Serena

Cross-file refactoring

Perform atomic renames, moves, and reference updates across large codebases without manual line-by-line edits.

Symbol-aware navigation

Quickly locate definitions, usages, and dependencies using semantic queries instead of text search.

Monorepo dependency analysis

Jump between related symbols and understand project structure in multi-language repositories.

How to use Serena

  1. 1Clone the Serena repository from GitHub.
  2. 2Follow the Quick Start instructions in the project README instead of marketplace commands.
  3. 3Configure your AI client to launch the Serena MCP server via stdio.
  4. 4Verify the connection in your client and test with a sample coding task.
  5. 5Optionally enable the JetBrains plugin for enhanced analysis on supported IDEs.

Serena: pros & cons

Pros

  • +Provides high-level semantic abstractions that reduce agent errors on large codebases.
  • +Evaluated positively by multiple agents across Python, Java, and multi-language projects.
  • +Works with a wide range of MCP-compatible clients including terminals and IDEs.
  • +Agent-first design focuses on reliability and efficiency over low-level primitives.

Cons

  • –Requires manual installation following project docs rather than simple marketplace setup.
  • –Tool list and exact parameters are only documented in external linked documentation.
  • –Depends on language server availability or JetBrains plugin for full functionality.
Did you find this helpful?

Frequently asked questions

No. The project explicitly warns against marketplace installs due to outdated commands and recommends following the official Quick Start.

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