"How to create Markdown files locally" matching MCP servers:

Provides access to markdown documentation for local NPM, Go, and PyPi packages as MCP resources or tools. It enables informed code generation by surfacing documentation directly from a project's working directory.

Enables agents to quickly find and edit code in a codebase with surgical precision. Find symbols, edit them everywhere with tools for reading code blocks, searching/replacing text, and making precise line-based modifications.

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 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.

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

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

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

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.

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.

Scans diffs, files, and snippets for leaked secrets like AWS keys, GitHub tokens, and private keys, returning redacted findings while running fully locally without network calls.

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

Deterministic navigation maps over code AND markdown for AI agents: one MCP server, two lenses (tree-sitter TS/JS/Python + markdown). Map a whole project, read one function or one doc-section, ~99% less context. Merges codelens + docslens.

MCP server connecting Claude Code to LM Studio, delegating token-expensive tasks to a local model while keeping the cloud model in control. It reduces cloud context usage by reading files locally and returning only the processed results.

Zero-config MCP server that connects local codebases to AI assistants, providing secure project tree, regex search, file reading, and tech stack tools locally.

Enables AI coding assistants to analyze codebases locally before generating code, reducing duplication and enforcing architecture boundaries.

Test coverage intelligence MCP server for TypeScript and JavaScript projects. Analyzes coverage reports to find untested functions, computes cyclomatic complexity, and suggests test cases locally.

Enables comparing Ruby hash literals and converting Ruby hashes to JSON with deterministic diff reports, running locally for privacy.

Visualize anything from Claude Code as a mermaid diagram in a locally hosted web app.

Enables running MegaLinter linting, configuration, and analysis through MCP tools. Works with any CI/CD platform or locally.