oraios/serena
by Various
A powerful MCP toolkit for coding, providing semantic retrieval and editing capabilities - the IDE for your agent
MCP
oraios/serena
Added 1 June 2026
Overview
Serena is an MCP toolkit written in Python that provides semantic retrieval and code editing capabilities for AI agents. It functions as an integrated development environment layer, enabling agents to search, understand, and modify code through natural language interfaces.
Best for
Best for
Developers building AI agents that need to understand and modify code programmatically
Use cases
- Semantic code search across large codebases
- Automated code refactoring and editing by agents
- Context-aware code retrieval for agent reasoning
How to use
Tools exposed
Capabilityrenameinline
Tested with
Claude Desktop, Claude Code, Cursor, VS Code
Notes
Serena is an MCP toolkit written in Python that provides semantic retrieval and code editing capabilities for AI agents. It functions as an integrated development environment layer, enabling agents to search, understand, and modify code through natural language interfaces.
24,823 stars on GitHub. Last updated 2026-06-01. Licensed MIT.
Use cases
- Semantic code search across large codebases
- Automated code refactoring and editing by agents
- Context-aware code retrieval for agent reasoning
Pros
- Semantic understanding of code rather than keyword matching
- Direct integration with MCP protocol for agent workflows
- Handles both retrieval and editing in one toolkit
Cons
- Python-only implementation limits language support
- Requires MCP-compatible agent framework to function
- Limited documentation on performance at scale
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Semantic understanding of code rather than keyword matching
- Direct integration with MCP protocol for agent workflows
- Handles both retrieval and editing in one toolkit
Cons
- Python-only implementation limits language support
- Requires MCP-compatible agent framework to function
- Limited documentation on performance at scale
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