MarkdownLM MCP Server

MarkdownLM MCP Server

Provides a persistent memory and governance layer that allows AI coding agents to query documented architecture rules and validate code against team standards. It enables agents to verify compliance across categories like security and testing before suggesting changes to ensure consistency across development sessions.

Category
Visit Server

README

<img src="assets/logo.png" width="48" height="48" style="vertical-align: middle; margin-right: 8px;"> MarkdownLM MCP Server

MarkdownLM is the persistent memory and governance layer between your team and your AI coding agents. Define your rules once. Enforced everywhere. Every session.

Note:

The MarkdownLM knowledge base supports the following categories for all rules, patterns, and decisions:

  • architecture: Layering, boundaries, system design
  • stack: Frameworks, libraries, versions
  • testing: Test frameworks, coverage, patterns
  • deployment: CI/CD, platforms, scripts
  • security: Auth, validation, secrets
  • style: Naming, formatting, organization
  • dependencies: Approved/banned packages
  • error_handling: Exceptions, logging, monitoring
  • business_logic: Domain rules, workflow constraints, business invariants, pricing logic, subscription rules, permission models
  • general: Anything else

When using this MCP server, always specify a category. category is a required field on query_knowledge_base.

How it works

  1. Your team documents architecture rules, stack decisions, and patterns in MarkdownLM.
  2. This MCP server gives AI coding agents three focused tools to query and validate against that knowledge.
  3. Agents validate code against your rules before suggesting changes — violations never reach PRs.

Setup

1. Get your API key

  1. Log in to MarkdownLM
  2. Go to Settings → API & MCP
  3. Generate an API key

2. Configure your AI tool

Pick your tool below. All use the same npm package — one codebase, every platform.


Claude Code (CLI)

claude mcp add markdownlm -e MARKDOWNLM_API_KEY=mdlm_your_key_here -e MARKDOWNLM_API_URL=https://markdownlm.com -- npx -y markdownlm-mcp

Or manually edit ~/.claude/claude_code_config.json:

{
  "mcpServers": {
    "markdownlm": {
      "command": "npx",
      "args": ["-y", "markdownlm-mcp"],
      "env": {
        "MARKDOWNLM_API_KEY": "mdlm_your_key_here",
        "MARKDOWNLM_API_URL": "https://markdownlm.com"
      }
    }
  }
}

Claude Desktop

~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%/Claude/claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "markdownlm": {
      "command": "npx",
      "args": ["-y", "markdownlm-mcp"],
      "env": {
        "MARKDOWNLM_API_KEY": "mdlm_your_key_here",
        "MARKDOWNLM_API_URL": "https://markdownlm.com"
      }
    }
  }
}

Cursor

.cursor/mcp.json in your project root (project-scoped) or ~/.cursor/mcp.json (global):

{
  "mcpServers": {
    "markdownlm": {
      "command": "npx",
      "args": ["-y", "markdownlm-mcp"],
      "env": {
        "MARKDOWNLM_API_KEY": "mdlm_your_key_here",
        "MARKDOWNLM_API_URL": "https://markdownlm.com"
      }
    }
  }
}

Windsurf

~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "markdownlm": {
      "command": "npx",
      "args": ["-y", "markdownlm-mcp"],
      "env": {
        "MARKDOWNLM_API_KEY": "mdlm_your_key_here",
        "MARKDOWNLM_API_URL": "https://markdownlm.com"
      }
    }
  }
}

Cline (VS Code)

In the Cline extension settings (MCP Servers):

{
  "mcpServers": {
    "markdownlm": {
      "command": "npx",
      "args": ["-y", "markdownlm-mcp"],
      "env": {
        "MARKDOWNLM_API_KEY": "mdlm_your_key_here",
        "MARKDOWNLM_API_URL": "https://markdownlm.com"
      }
    }
  }
}

VS Code (Native/Extension)

.vscode/mcp.json in your project root:

{
  "servers": {
    "markdownlm": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "markdownlm-mcp"],
      "env": {
        "MARKDOWNLM_API_KEY": "mdlm_your_key_here",
        "MARKDOWNLM_API_URL": "https://markdownlm.com"
      }
    }
  }
}

Tools

query_knowledge_base

Query your team's documented rules before writing code. Returns relevant rules with sources and automatically logs gaps for undocumented decisions.

Inputs

Field Required Description
query Natural language question (e.g. "How should I handle auth?")
category Category of the query: architecture, stack, testing, deployment, security, style, dependencies, error_handling, business_logic, general

Responseanswer, sources[], gap_detected, optional gap_resolution


validate_code

Validate a code snippet against all documented rules. Returns pass/fail with violation details and fix suggestions.

Inputs

Field Required Description
code Code snippet to check
task What the code is supposed to do
category The knowledge base category relevant to this code

Responsestatus (pass/fail), violations[] (rule, message, fix_suggestion), fix_suggestion


resolve_gap

Log a knowledge gap for an undocumented decision. Returns how to handle it based on your preferences: markdownlm (AI resolves), ask_user (wait for human), agent_decide (proceed independently).

Inputs

Field Required Description
question The undocumented decision or question
category Category hint

Responsegap_detected, resolution_mode, optional resolution, gap_id


Environment variables

Variable Required Default Description
MARKDOWNLM_API_KEY API key from Settings → API & MCP
MARKDOWNLM_API_URL https://markdownlm.com Override for self-hosted or staging

Rate limiting

100 tool calls per 60 seconds per user.

Logging

All tool calls are logged to stderr as newline-delimited JSON (timestamp, tool name, inputs, outcome). This is safe for stdio MCP transport and can be piped to any log aggregator.

Contributing & Security

This repository is strictly the bridge (the client), not the brain. To protect our intellectual property, infrastructure details, and customer data, please carefully review our Contributing Guidelines and Security Policy before making any modifications.

License

Copyright (c) 2026 MarkdownLM. All Rights Reserved.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured