"Enhancing Markdown (.MD) file editing capabilities" matching MCP servers:

A Model Context Protocol (MCP) server for validating Mermaid diagram syntax and providing comprehensive grammar checking capabilities

Enables AI models to access and search offline Wikipedia and other knowledge bases stored in ZIM format files. Provides intelligent content retrieval, structured browsing, advanced search capabilities, and metadata extraction for comprehensive offline knowledge access.

Enables AI assistants to generate real images via multiple models (OpenAI, Gemini, Recraft, Seedream, Grok, Arrow) and returns usable file paths instead of base64 data.

Enables fast literal and regex search over local workspaces using a sparse n-gram index for candidate pruning, with deterministic verification against file contents.

Gives AI assistants a read-only, offline interface to the FinOps Foundation's published guidance — its principles, phases, domains, 22 capabilities with Crawl/Walk/Run maturity assessments, personas, and an 88-entry KPI library — so FinOps questions are answered with the Foundation's own text and formulas rather than improvised ones. It exposes 11 tools, document resources, and four guided prompts over stdio, with every response carrying its source URL and license.

Enables MCP clients to score retrieval quality with recall, precision, nDCG, hit rate and MRR, compare 2-3 configurations with seeded paired-bootstrap confidence intervals, audit agent tool calls against expected traces, and detect prompt regressions against golden sets. It also generates Markdown, JSON or JUnit reports with pass/fail gates, all deterministically and offline without paid API keys.

Enables MCP clients to send prompts anonymously to ChatGPT and receive the markdown answer plus the web sources it consulted as structured JSON. Requires only a HasData API key, with no OpenAI account, API key, or billing needed.

A simple MCP server that provides a basic greeting tool and serves as a starter template for AWS Lambda deployment. Demonstrates how to build and deploy MCP servers with both local development and cloud deployment capabilities.

Git-native long-term memory for AI agents: your markdown files are the source of truth, the search index is a disposable projection rebuilt from git, and every memory the agent writes is a reviewable git commit. Served over one OAuth-secured MCP endpoint with hybrid lexical+semantic recall and a gated, git-first commit_note write tool.

Extract invoices and contracts from text or Markdown into typed JSON with Mistral. Optional OCR supports PDFs and images when your account has access and quota. Six tools by default: documents, OCR, chat, vision, code completion and transcription. Additional API tools via explicit profiles. Runs over stdio or Streamable HTTP. Community-maintained; bring your own Mistral API key.

Enables listing top-level frames in a Figma file and fetching a selected frame's rendered PNG, node JSON, and image-fill map into a local output directory.

An MCP server that fetches web pages and extracts clean, AI-friendly Markdown content using Mozilla Readability. It provides secure web access for LLMs with built-in SSRF protection and automated content cleaning for improved context retrieval and summarization.

A MCP server for querying the VirusTotal API. This server provides tools for scanning URLs, analyzing file hashes, and retrieving IP address reports.

Enables an MCP client to read Telegram through your own account — searching and reading chats, folders, forum topics, threads, albums, reactions, and polls, plus discovering public channels — without sending messages or marking anything read. It also supports durable change checkpoints, named watch subscriptions, and source-linked JSONL/Markdown history exports.

Enables AI assistants to turn local git history into answers about recent activity, file hotspots, change coupling, stale or already-merged branches, contributors, ref comparisons, and drafted release notes. It runs locally over stdio with a git subcommand allowlist, so it is read-only, works offline and without shell access, and is safe to auto-approve.

Enables AI-driven interior, exterior, and landscape design, photoreal rendering, image editing, video generation, and 3D model creation directly inside Claude, Cursor, VS Code, and other MCP clients. It also supports virtual staging, sketching to render, texture and pattern generation, background removal, and architectural consultation through natural language.

Enables LLMs to inspect schemas and execute SQL queries on Peaka projects using Peaka's text2SQL capabilities.

Provides AI assistants access to live Material Design 3 documentation including Foundations, Styles, and Components, returning official content as Markdown.

A Python MCP server for web research that enables fetching web pages, searching, batch-fetching, extracting links, and summarizing content via client-side sampling, with optional local file access.

A server providing tools for querying and analyzing Teradata databases, including database management, data quality assessment, and SQL execution capabilities through an MCP interface.