Query current session cost across AI coding tools like Claude Code and Cline without requiring an API key.
MIT
675,423 tools. Updated 2026-10-19 05:13
"Coding tools to understand and manage a large codebase like MCP, CLINE, or ROOCODE" matching MCP tools:
- Get a comprehensive repository blueprint: README, top dependencies, key functions/variables, and coding conventions. Understand any codebase at a glance.MIT
- Analyze a repository to reveal project type, languages, file sizes, module dependencies, and circular import warnings. Use this to understand the codebase structure before making changes.AGPL 3.0
- Check connected variants' port, connection status, available tools, and reconnect timing. Call before using other tools to understand what's available.Apache 2.0
- Orient a coding agent on a repository by retrieving a JSON project overview with absolute root, git root, and counts of files, symbols, dependencies, and languages. Use this first to understand codebase size.MIT
- Retrieve design rules inferred from codebase patterns. Filter by category to understand implicit conventions for spacing, colors, typography, and more before building.Apache 2.0
Matching MCP Servers
- AlicenseNot gradedqualityBmaintenanceGives any MCP-compatible AI chat or agent a safe, model-neutral coding runtime with file read/search, structured multi-file patches, command execution, interactive sessions, and git operations, all confined to a single workspace and gated by permission modes.Apache 2.0
- AlicenseNot gradedqualityBmaintenanceEmpower any MCP-compatible AI Agent(MCP Client) with engineering-grade capabilities to understand, modify, run, and deliver real-world code repositories.212 PyPI1,194Apache 2.0
Matching MCP Connectors
Let your AI agent build, preview and update web apps, download source and publish when you allow it.
Suggest ICD-10-CM codes from a diagnosis description. Returns ranked codes with confidence, reasoning, coding notes, differential alternatives.
- Generate a comprehensive codebase architecture map showing modules, dependencies, frequently changed files, and API endpoints to understand structure before starting development tasks.MIT
- Returns aggregate statistics for a repository, including total file count and a breakdown by programming language. Use this to understand the tech stack and codebase scale.MIT
- Gather requirements and research codebase to generate an actionable plan for execution. Retrieve existing plans to view progress.MIT
- View a project's directory tree to understand its structure, locate files, or navigate the codebase. Use optional filters to narrow by path or highlight files containing specific keywords.MIT
- Detect coding conventions in a project before adding new code, ensuring your changes align with established patterns.MIT
- Access documentation and usage guides for n8n workflow automation tools to understand available capabilities and implementation methods.MIT
- Generate project-consistent identifier names from a natural language description. Uses actual conventions like prefixes and patterns to suggest names that fit the existing codebase style. Use when naming functions, variables, or parameters.MIT
- Visualize the semantic topology of your codebase to identify which directories concentrate domain concepts, including entity counts and density, for a quick understanding of codebase layout before detailed analysis.MIT
- Understand large codebases by sending a prompt; receive a structured analysis report with key findings and code insights.MIT
- Search indexed AI coding-agent conversation threads from multiple tools to recall past decisions, prior solutions, or earlier discussion. Supports keyword and hybrid semantic search.AGPL 3.0
- Discover available series codes, names, units, and frequencies from Bank of Japan databases to understand database structure before fetching actual data. Use layer-based queries for large databases.MIT
- Routes coding tasks to the best available model based on complexity, handling code generation, refactoring, and algorithm design with optional system prompts and context.MIT
- Trigger a full codebase reindex to update semantic search embeddings after significant code changes or when the index appears outdated.MIT
- Retrieve coding patterns and conventions for the codebase, including naming, structure, and idioms. Optionally filter by query. Follow existing conventions before writing new code.AGPL 3.0
- Analyze any repository to get a high-level map including languages, frameworks, size, structure, and entry points. Understand unfamiliar codebases quickly.MIT