"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 agents and tools to access Markdown linting through the Model Context Protocol, providing structured lint results and workspace-aware checks.

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.

Lets AI coding agents read an outline of a large file or a digest of noisy command output instead of the full text, while every hidden line stays retrievable on disk through a run handle. Agents can request only the line ranges, slices, or grep matches they need and list recent runs, cutting token spend without losing information.

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.

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.

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

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.

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.

Enables AI agents to browse, read, search, blame, and diff files from any branch, tag, or commit in a self-managed GitLab instance without checking anything out or modifying the working tree. Content is served read-only from locally cached git mirrors or your own clones, so no GitLab REST API access is needed.

An MCP server that indexes a repository locally and provides keyword, semantic, hybrid, and SQL search tools, enabling coding agents to answer questions about the codebase efficiently without reading files one by one.

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.

Enables MCP-compatible AI clients to generate markdown documentation for single code files or batches of up to 20 files, using a Writulos Scribe API key.

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.

Lints local Markdown files or whole directory trees for broken relative links and images, empty link targets or text, heading hierarchy problems, and common README issues. Only relative targets on disk are checked, so external http(s) links are never fetched.

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 AI coding agents to read, review, and test ABAP code stored as abapGit files without an SAP system. Agents can list and outline objects, check Clean ABAP conventions, run full static analysis, and execute ABAP Unit tests locally on a laptop.

Enables AI coding agents to perform evidence-based, read-only audits of supported software projects by exposing bounded project inventory and static-analysis findings for discovery, code review, integration tracing, security, and tests. Reports are returned as Markdown or JSON directly in the tool response, with no code executed or files written.

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

Turns a local project folder into a searchable second brain that indexes code symbols, dependencies, notes, PDFs and web snapshots, then exposes hybrid keyword and embedding search, graph traversal, impact analysis and architecture reports to MCP clients. It also lets assistants record and recall architectural decisions and learnings as Markdown, so project memory persists across conversations, all running locally through one shared HTTP service.