"Using Code to Create a PowerPoint Presentation" matching MCP servers:

A runtime-free MCP server that converts source code into AST🌲, regardless of language.

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.

MCP server with local vector search for your codebase. Smart indexing, semantic search, Git history — all offline.

A local MCP server that provides semantic code search for Python codebases using tree-sitter for chunking and LanceDB for vector storage. It enables natural language queries to find relevant code snippets based on meaning rather than just text matching.

embedded code search engine CLI -AST based that just works - improves speed and efficiency for coding agent

Enables efficient analysis of large codebases using Claude Code and Kimi K2.5 through the Model Context Protocol, with session caching and parallel processing to reduce costs and time.

An MCP server that provides dynamic codebase context to Claude Code through tools like hybrid search, recent changes, and symbol definitions, enhancing AI-assisted coding with local RAG.

Gemini-powered MCP server for automated code review, analysis, and documentation.

Fast pre-commit dependency gate for AI-assisted code changes. Answers "is this safe to commit?" with a PASS/WARN/BLOCK verdict in seconds, so you can catch risky blast radius before a bad commit, not after it. No database, no heavy setup.

Indexes a mono-repo into a knowledge graph and provides MCP tools to query code structure—packages, components, routes, HTTP calls—without file reads or grep round-trips.

Connects Kimi Code with Claude Code, enabling Claude to delegate bulk codebase reading to Kimi (256K context) for cost savings, while Claude focuses on reasoning and code edits.

Provides structural, queryable understanding of a Python codebase via MCP tools, enabling direct lookups for callers, dependencies, and class hierarchies without repeated grep/read cycles.

A self-hosted semantic code retrieval MCP server that enables natural language queries to find relevant code snippets using Tree-sitter AST parsing, embedding, and hybrid search with reranking.

A security filter that blocks dangerous code patterns by comparing normalized structural syntax trees against a blacklist of known threats using vector embeddings. It acts as a gatekeeper to prevent malicious code execution by identifying dangerous structures regardless of specific identifiers or literals.

A production-grade MCP server for the Code-Fundi API, enabling AI agents to map codebases, search semantically, and analyze blast radius. It provides tools for repository management, AI-powered research, and impact analysis before shipping changes.

An MCP server that acts as a context-aware code retrieval broker for AI coding agents, enforcing backpressure and token budgeting to prevent context window overflow.

Enables comprehensive code analysis including quality assessment, security vulnerability detection, refactoring suggestions, complexity calculations, and automatic documentation generation for multiple programming languages.

Enables LLMs to efficiently read, write, and refactor code using precise AST-based operations, reducing token usage and context window waste.

An MCP server that automates code review by providing syntax checking, code explanation, and improvement suggestions using a multi-agent system.

An MCP server that indexes source code into a local database and provides tools for querying code symbols, dependencies, and tree structure for JavaScript/TypeScript, Java, and Python.