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Serena MCP usage guide for semantic code operations, symbol manipulation, project memory, and session persistence. Use when invoking any mcp__serena__* tools, performing symbol operations (rename, find references, extract), navigating large codebases, or managing project memory/sessions.

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SKILL.md

name serena
description Serena MCP usage guide for semantic code operations, symbol manipulation, project memory, and session persistence. Use when invoking any mcp__serena__* tools, performing symbol operations (rename, find references, extract), navigating large codebases, or managing project memory/sessions.

Serena MCP Server

Semantic code understanding with project memory and session persistence.

Required First Step

ALWAYS activate project before any Serena operation:

mcp__serena__activate_project(project: "<path_or_name>")
mcp__serena__check_onboarding_performed()

When to Use Serena

Use Case Serena Alternative
Symbol rename with references ✅ ❌ Morphllm
Find all references ✅ ❌ Grep
Semantic code navigation ✅ ❌ Native
Project memory/session ✅ ❌ None
Pattern-based bulk edits ❌ ✅ Morphllm
Simple text replacement ❌ ✅ Edit tool

Core Tools

Project Lifecycle

  • activate_project → REQUIRED FIRST - activate target project
  • get_current_config → check active project and available tools
  • check_onboarding_performed → verify project is ready
  • onboarding → run if onboarding not yet performed

Symbol Operations

  • find_symbol → locate symbols by name path pattern
  • find_referencing_symbols → find all references to a symbol
  • get_symbols_overview → high-level view of file symbols
  • rename_symbol → rename across entire codebase
  • replace_symbol_body → replace symbol definition
  • insert_before_symbol / insert_after_symbol → add code around symbols

Search & Navigation

  • search_for_pattern → regex search across codebase
  • list_dir → list directory contents
  • find_file → find files by mask

Memory Management

  • write_memory → persist information for future sessions
  • read_memory → retrieve stored information
  • list_memories → show available memories
  • edit_memory / delete_memory → modify or remove memories

Reflection (Call These!)

  • think_about_collected_information → after search operations
  • think_about_task_adherence → before code modifications
  • think_about_whether_you_are_done → at task completion

Tool Details

See references/tools.md for detailed parameter documentation.

Workflow Patterns

Session Start

1. activate_project(project: "path/to/project")
2. check_onboarding_performed()
3. list_memories() → check existing context
4. read_memory("relevant_memory") → if applicable

Symbol Investigation

1. get_symbols_overview(relative_path: "file.py", depth: 1)
2. find_symbol(name_path_pattern: "ClassName", include_body: false)
3. find_symbol(name_path_pattern: "ClassName/method", include_body: true)
4. think_about_collected_information()

Symbol Modification

1. find_symbol(name_path_pattern: "target", include_body: true)
2. think_about_task_adherence()
3. replace_symbol_body(name_path: "target", relative_path: "file.py", body: "new code")

Cross-Session Persistence

1. write_memory("task_context", "important findings...")
2. [end session]
3. [new session]
4. activate_project(...)
5. list_memories()
6. read_memory("task_context")

Name Path Patterns

Pattern Matches
method Any symbol named "method"
Class/method method inside Class
/Class/method Exact path from file root
Foo/get with substring_matching: true Foo/getValue, Foo/getData

Best Practices

  1. Activate first - Always activate_project before operations
  2. Read before edit - Use find_symbol with include_body: true before modifications
  3. Use reflection tools - Call think_about_* tools at appropriate points
  4. Prefer symbolic over text - Use symbol tools over grep/edit when possible
  5. Persist important context - Use memory for cross-session continuity