Refresh codebase context by analyzing React/TypeScript/Node.js projects and generating structured bundles with component summaries, dependency information, and a snapshot ID for AI-assisted analysis.
MIT
458,064 tools. Updated 2026-08-14 20:18
"Using a TypeScript codebase as context for a tool or service" matching MCP tools:
- Search codebase for code structure using Tree-sitter AST patterns. Scans all files to match structural elements like functions or classes. Requires glob to limit scope.MIT
- Returns a TypeScript snippet to mark a transaction as delivered (IN_PROGRESS → DELIVERED) after specifying the deliverable. Running the code triggers the requester dispute window.Apache 2.0
- Request a service from an AGIRAILS agent by generating a TypeScript snippet that initiates an ACTP transaction. Funds are not locked until you accept the quote.Apache 2.0
- Ask programming questions and get explanations from Kimi's model without codebase context. Use for algorithms, code reviews, or general coding advice.MIT
- Search multiple codebases in parallel using natural language. Returns results grouped per codebase or a single globally-ranked list across all repositories.Apache 2.0
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- Generates suggestions for improving your app (UX, performance, retention) and your idea (positioning, monetization) by analyzing project context or codebase.MIT
- Check project state—index health, memory summary—and get tool recommendations for the codebase. Use this first in a new session to understand project context.MIT
- Submit a structural code map of your codebase to VibeMap. Define nodes for pages, APIs, models, and edges for imports, routes, reads, writes.MIT
- Analyze error logs and stack traces to extract relevant code context from your project, using semantic embeddings and symbol matching to provide structured debugging insights.MIT
- Verify TypeScript code correctness by running type-checking on a specified service path, receiving structured error details for pre-commit validation.MIT
- Get answers to questions about any codebase using AI with full repository context. Combines static analysis and key file contents for evidence-based responses.MIT
- Generates a ranked outline of a codebase, highlighting key files and symbols to orient AI agents in unfamiliar projects. Focuses on dependencies and dependents using PageRank.Apache 2.0
- Search across the codebase to locate all usages of a component, hook, or service, including imports and JSX/template references, for impact analysis.MIT
- Ask general programming questions, get algorithm explanations, or obtain a second opinion without codebase context.MIT
- Find the most relevant Token Savior tools for a task using natural-language queries, returning full schema or TypeScript signatures for direct use.MIT
- Search codebase content rapidly using ripgrep with regex patterns, file type filters, and context lines for precise code analysis.MIT
- Analyze a remote directory to identify technical environments and read dependency manifests, giving architectural context of a codebase.MIT
- Scan project files to build a code graph: extracts definitions and resolves call/import relationships across Python, TypeScript, and JavaScript. Use force for a full rebuild or view indexing stats.MIT
- Analyze a codebase with tree-sitter to produce a structured architectural payload for code review, refactoring, planning, or Q&A. Includes AST analysis, change detection, and caching.MIT