{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/16"}],"enrichment":{"capability":"Serena is an MCP server that provides semantic code retrieval, editing, and refactoring tools for AI coding agents, operating at the symbol level across over 40 programming languages via language servers or JetBrains IDE integration.","skillfed_tags":["mcp-server","ai-coding-agent","semantic-code-tools"],"use_cases":["Enable an AI agent to safely rename symbols across multiple files in a large codebase without manual line-by-line verification","Let a coding agent explore and understand a monorepo's structure by querying symbols and their relationships at the semantic level","Provide an agent with IDE-backed diagnostics and inspections to catch errors before suggesting code changes","Support multi-language projects where agents need consistent symbol-aware navigation across Python, Java, TypeScript, and other languages","Reduce agent hallucination and errors by replacing fragile text-based edits with atomic, symbol-aware refactoring operations"],"what_it_does":"Serena is an MCP (Model Context Protocol) server designed to give AI coding agents IDE-level capabilities for understanding and modifying code. Instead of working with raw text and line numbers, agents using Serena can perform semantic operations like finding symbols, cross-file renames, reference lookups, and refactoring\u2014all grounded in the actual structure of the code. It supports over 40 programming languages through an abstraction layer over language servers (the free/open-source default) or optionally through JetBrains IDE integration (paid with free trial).\n\nThe package integrates with modern AI chat clients\u2014Claude Code, Codex, Copilot, JetBrains AI Assistant, and others\u2014via MCP. You either launch Serena as a subprocess or run it in HTTP mode and point your client to it. The tool is built for agent-first workflows: it provides high-level abstractions that let agents work faster and more reliably on complex codebases by reducing error-prone manual text surgery into atomic, semantically-aware operations. It includes 33 runtime dependencies covering web frameworks (flask, starlette), LLM integration (anthropic, tiktoken), code parsing (beautifulsoup4, pyyaml), and protocol support (lsprotocol, pygls, mcp).","worth_installing":"Yes, with conditions. Serena is actively maintained, has low install friction, carries no security vulnerabilities, and is MIT-licensed. It is worth installing if you are running an AI coding agent in a modern client that supports MCP and need IDE-level code understanding to improve agent reliability and speed. Not worth installing if you are not using an MCP-compatible AI client or if your codebase is small enough that agents work well with built-in text-based tools. The 33 runtime dependencies are substantial; verify they do not conflict with your environment."},"id":"serena-agent","links":{"html":"https://skillfed.io/packages/serena-agent","md":"https://skillfed.io/packages/serena-agent.md","pypi":"https://pypi.org/project/serena-agent/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-09","license_spdx":null,"license_treatment":"permissive","name":"serena-agent","python_support":"supports_current","summary":"A powerful MCP toolkit for coding, providing semantic retrieval and editing capabilities - the IDE for your agent"},"popularity":{"monthly_downloads":115155,"position":12266,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.7.0"}