"A platform for cloud storage and file management" matching MCP servers:

Enables blazingly fast file and content searching in large codebases using ripgrep, with intelligent filtering, fuzzy finding, and directory tree visualization while respecting .gitignore and avoiding common bloat directories.

Reduces Claude's context window costs by automatically summarizing inactive files to their public interfaces using AST parsing, keeping only the full contents of the currently active file.

Enables AI agents to explore, analyze, and search file systems, with tools for directory trees, file statistics, duplicate detection, code counting, and multi-criteria file search.

Provides deep git file-level forensics tools to analyze detailed file histories, changes, and patterns within git repositories, focusing on individual file analysis rather than repository-wide operations.

Analyzes codebases for cross-platform compatibility issues, detecting platform-specific APIs, file path problems, line ending inconsistencies, and shell command incompatibilities across Windows, macOS, and Linux.

Provides a local SQLite-backed code context knowledge base with MCP tools for storing and querying code facts, call graphs, semantic info, evidence, and business mappings, plus versioned snapshot publishing and incremental sync.

An MCP server that provides a flexible lens into directory structures and files, enabling LLM clients to efficiently navigate and understand codebases with minimal noise. It offers secure, gitignore-aware file access with tools like directory listing, file reading, and grep-like search.

Enables precise file patching using SEARCH/REPLACE blocks, with mandatory directory sandboxing, automatic Python QA (Ruff/Black/MyPy), and git versioning for rollback.

Enables intelligent handling of large files through smart chunking, search with regex support, line navigation, and streaming capabilities without loading entire files into memory.

MCP server for the Codex Security Cloud service, enabling agents to list, inspect, close, reopen findings, request PRs, and apply generated patches.

Enables AI assistants to read Bitbucket Cloud pull requests and diffs through natural conversation.

A Model Context Protocol server that helps programmers understand code by providing explanations, tech stack analysis, and best practice suggestions through prompt templates.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

Enables AI agents to analyze and search IFS Cloud codebases using hybrid semantic-lexical search, PageRank importance ranking, and dependency graph analysis. It supports comprehensive exploration of PL/SQL, entities, and projection files to facilitate intelligent architectural understanding.

Audits dbt Core projects for migration blockers and generates actionable guidance for migrating to dbt Cloud, including auto-fixing deprecated syntax.

Integrates Google's Gemini AI models into Claude Code and other MCP clients to provide second opinions, code comparisons, and token counting. It supports streaming responses and multi-turn conversations directly within your existing AI development workflow.

Enables read-only auditing of repositories by scanning actual files, flagging risky code, secrets, and untrusted platform configs, and generating Chinese-language reports for human decision-making.

Provides AI agents with ground-truth knowledge of Strapi projects by reading real schema files, enabling accurate queries and safe refactoring operations.

Enables MCP-compatible AI clients to inspect Godot project and editor state, observe opted-in running scenes, manage processes, and apply permission-scoped guarded edits. It starts read-only and exposes additional capabilities only through explicit command-line flags.

Enables analysis of multi-file git workspaces to synthesize dependency diffs and refactor sequences.

Uses Claude as an independent second-model reviewer inside Codex, performing reviews on disposable Git snapshots with structured findings.

Enables MCP clients to list workspaces and inspect concise, workspace-scoped code review findings and hosted run summaries. It can also prepare a hosted review for an open pull request and, after explicit user confirmation, start or rerun it, without exposing raw diffs, reports, or credentials.

Enables Claude Code to leverage OpenAI models for expert code review, deep architecture analysis, and security audits, with automatic markdown report generation.

Enables an MCP client to sign in and inspect workspace-scoped review findings and hosted runs, and to prepare, then start or rerun after explicit confirmation, an existing hosted code review for a pull request. It exposes only concise summaries, never raw diffs, full reports, artifacts, credentials, or prompt text.

Codebase Q&A agent with git-history awareness. Explore a repo with list_files, read_file, and search, plus git log, blame, and diff and a repo map to answer "why did this change?" questions. Runs locally as an MCP server for Claude Code and other MCP clients.

Analyzes source code structure across multiple languages using tree-sitter, extracting classes, functions, methods, and metadata with precise line numbers for efficient codebase exploration and AI-assisted development.

A remote, OAuth-protected server that lets MCP clients list workspaces, inspect concise review findings and hosted run summaries, and prepare or, after explicit confirmation, start and rerun existing hosted reviews without exposing raw diffs or full reports.

Enables authenticated MCP clients to browse their Juror workspaces, inspect workspace-scoped review findings, and summarize open P0/P1 issues. It can also prepare and, after explicit user confirmation, start or rerun an existing hosted Juror Cloud review, without exposing raw diffs, reports, or credentials.

Inspects workspace-scoped review findings and hosted runs, and can prepare and, after explicit user confirmation, start or rerun an existing hosted review. It avoids exposing raw diffs, full reports, artifacts, screenshots, credentials, or arbitrary local repository access.