"How to manage schedules and to-do lists on a Mac" matching MCP servers:

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

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

Enables automated migration of Vue projects to React with intelligent analysis, task management, and learning from user modifications.

Enables Claude to use Google Gemini as a secondary AI through MCP for large-scale codebase analysis and complex reasoning tasks. Supports both Gemini Flash and Pro models with specialized functions for general queries and comprehensive code analysis.

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.

Enables AI coding agents to extract Figma design data and convert it into Flutter widgets and screens. Supports theme setup, component analysis, asset exports, and provides Flutter implementation guidance from Figma designs.

Enables AI assistants to analyze project folders for dependencies and frameworks and fetch current documentation or datasheets from the web.

Enables migration of test automation projects from WebDriverIO to Playwright using AST-based transformations. Provides tools for analyzing tests, converting syntax, refactoring to Page Object Model, and generating migration reports.

Converts vector PDF circuit schematics into evidence-preserving SchematicIR JSON with tools to inspect, convert, and validate schematic PDFs.

Enables MCP clients such as Claude Desktop or Cursor to inspect a coffee-shop sales database schema, validate SQL, and run guarded read-only queries. It supports natural-language questions by exposing tools for schema description, SQL checking, and safe query execution.

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.

locidx

A lean, local knowledge graph that joins a repo's code to its aSPARK delivery artifacts, enabling agents to trace user stories to code and assess impact of changes, served over MCP.

Enables interaction with SAP ABAP systems via ADT APIs, allowing management of ABAP objects, transport requests, and code analysis through MCP clients.

Enables AI agents to analyze and diff binaries by driving Ghidra headless or inside its GUI, exposing native reverse-engineering tools such as listing functions and segments, searching strings, decompiling, disassembling, and following cross-references. Ships with a devcontainer and supports local stdio or remote HTTP deployment.

Enables MCP clients to load eight on-demand coding skills and inspect project repositories through bounded, read-only map, search, read, diff, checks, and style tools. It keeps context lean by loading skill bodies only when needed and limiting repository scan and output sizes.

Enables executing arbitrary Joern/CPGQL queries against a loaded Code Property Graph, loading source code in multiple languages (PHP, Java, JavaScript, Python, C/C++) to build new CPGs, and inspecting loaded projects and the active workspace. It communicates with a running Joern server over its synchronous HTTP query endpoint, so no state polling is required.

Zero-dependency MCP server inspector for protocol conformance, tool annotations, and capability checks.

coldstart gives coding agents durable memory of a specific codebase, with no embeddings, no vector store, and no API key. Agents write notes after real tasks — what a file is for, how a flow spans files, which invariants hold — and those notes are surfaced automatically to a later session whose task matches, so nothing gets rediscovered from scratch. Every note is anchored to real files by content

Twelve tools combine per-function complexity and branch coverage to rank work and check edited functions against their ceiling. Packets include source, uncovered lines, change-coupled files and near-duplicates. MCP calls can write local caches and metadata; they do not run test suites, edit source or claim work.

Call graph MCP server for Rust, Python, TypeScript, TSX, and JavaScript. Every caller and callee carries a resolution field showing how the reference was matched to a definition, plus multi-hop impact analysis for refactoring. Local-only, single binary, no network egress. Benchmarked against grep, ripgrep, and ctags on a 120-item hand-verified golden set, including the cases where it loses.

Enables an AI assistant to debug ABAP code on a connected SAP system by setting breakpoints, running code, and capturing call stacks and variables, with one-shot or interactive stepping.

Architectural sensor for Python codebases. Scores structural health (modularity, acyclicity, depth, equality), detects import cycles, enforces YAML layer rules, and runs a snapshot/diff loop so AI-assisted edits do not silently regress structure.

Enables AI coding agents to submit work for external review before declaring a task done, receiving evidence-backed fix lists and verdicts based on git-measured changes and calibrated quality scoring.

Enables AI agents to lint API artifacts (OpenAPI, AsyncAPI, Arazzo) and manage rulesets conversationally via the Model Context Protocol.

Translate Python between English and your language, with round-trip verification. Pack-based and reviewed, not model-guessed: translate files both ways, look up how terms render, check identifier names, and report how legible a codebase is in a language, all locally with uvx legesher-mcp.

An MCP server that connects Gemini 2.5 Pro to Claude Code, enabling users to generate detailed implementation plans based on their codebase and receive feedback on code changes.

A powerful tool designed to help, primarily LLMs, understand and navigate complex codebases. It functions both as a command-line application for on-demand analysis and as an MCP (Model Context Protocol) server, providing continuous repository mapping capabilities to other applications. By generating

A codebase ontology and a cited wiki, both kept as Markdown in one folder on your disk. Typed graph answers — what a change affects, how two concepts connect, which wiki lines lack a citation — and every write lands as a Git diff a person reviews.

Enables analysis of GitHub Pull Requests, including details, diff, file lists, and review tracking.