Code Fundi
Code Fundi is a codebase intelligence platform that powers AI agents, engineering teams, and applications with a searchable map of software repositories. Instead of relying on grep, raw embeddings, or disconnected documentation, it ingests a repository from a URL or GitHub, maps files, functions, dependencies, and logic flows, removes boilerplate noise, and converts the result into a token-optimized representation ready for AI context windows. Its Blast-Radius Guard shows which files, services, and downstream behaviors may be affected before an agent changes code, helping teams prevent silent regressions and production failures. Universal Search runs sub-second semantic queries across one repository or hundreds of codebases, allowing users to find implementation patterns, compare architectures, inspect authentication or testing strategies, and trace how code works across projects.
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Grep
Grep by Vercel is a code search tool that allows users to search for code, files, and paths across half a million public GitHub repositories. It supports searching by regular expressions, enabling precise and flexible queries.
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Maguyva
Maguyva is agent-first code intelligence that gives AI coding tools a ranked map of a repository before they start editing. Teams connect GitHub repositories, and cloud pipelines parse, rank, and index symbols, dependencies, imports, semantic relationships, and cross-file structure, then keep the index current as code changes. Through one remote MCP integration, agents in Claude Code, Cursor, VS Code, Windsurf, Codex, Gemini CLI, and other compatible clients can query the same grounded context without installing a local indexer or changing editors. Its 11 MCP tools combine semantic, structural, graph, and text retrieval across five search modalities, returning ranked results instead of raw grep output. Agents can ask plain-language questions, locate important symbols, find patterns through AST-aware search, trace dependents, identify orphaned code, analyze a change’s blast radius, and assemble task context before touching a file.
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Muse Code
Muse Code is Meta’s terminal coding agent, powered by Muse Spark 1.2, for handling complex software engineering tasks across large repositories. The agent can plan changes, write code, validate results, and coordinate multiple persistent subagents during development sessions. Muse Code uses async background agents that stay active throughout a session to reduce repeated information gathering and help complete multi-step tasks with less steering. Its runtime uses a local event log that records model calls, tool runs, approvals, and edits so sessions can be replayed and resumed after failures. Muse Code includes bundled skills such as /plan for approval-gated planning, /grill for stress-testing plans, and /goal for working toward completion. Built for AI developers and software teams, Muse Code helps automate coding workflows, long-running engineering tasks, debugging, and repository-level development.
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