Terragrunt-Docs
Terragrunt documentation always up to date.
MCP Server: Terragrunt Docs Provider
A Model Context Protocol (MCP) server built with Deno and TypeScript, designed to provide contextual information related to Terragrunt.
Overview
This server acts as an MCP provider, exposing tools and resources that allow AI agents or other MCP clients to query information about Terragrunt documentation and development information, such as GitHub issues.
- Watch a realistic demo 📺 on Claude Desktop here
Why?
When writing IaC configurations, mostly in terragrunt, the IDE support isn't that good, in VSCode the terraform plugin is good, but not for terragrunt; it does not recognize the terragrunt blocks and does not provide any autocompletion. When interacting with AI autocompletion, it's common to get incorrect results, or false-positive linting errors. With this MCP server, you can provide to your LLM/AI assistant the latest documentation and issues from the Terragrunt GitHub repository, so it can use that to provide you with the most accurate information.
Tools
Note: All tools require a valid GitHub token set as an environment variable:
GITHUB_TOKEN,GH_TOKEN, orGITHUB_PERSONAL_ACCESS_TOKEN.
| Tool Name | Purpose | Inputs | Outputs | Use Case |
|---|---|---|---|---|
list-doc-categories | Retrieve all documentation categories from Terragrunt docs. | None | Array of objects with name (string) and link (string) properties | Use when you need to explore the available documentation structure or when building a documentation navigation system. This is typically the first tool to call when starting to work with Terragrunt docs. |
list-all-docs-by-category | List all docs in a specific category. | category (string) | Array of objects with name (string), link (string), and content (string) | Use when you need to see all available documentation within a specific category, such as when building a category-specific documentation viewer or when you need to scan through all docs in a particular area. |
read-document-from-category | Read a specific doc from a category. | category (string), document (string) | Object containing content (string) with the full markdown content | Use when you need to access the complete content of a specific document, such as when implementing documentation search or when you need to reference specific documentation in your application. |
read-all-docs-from-category | Retrieve and merge all docs in a category into one response. | category (string) | Object containing content (string) with all docs merged into one | Use when you need a comprehensive view of all documentation within a category, such as when building a documentation search feature or when you need to analyze the complete documentation set for a specific topic. |
get-all-open-issues | Retrieve all open issues from Terragrunt GitHub repo. | all (boolean, optional) | Array of objects with title (string), number (number), state (string), created_at (string), updated_at (string), body (string), and labels (string[]) | Use when you need to track or analyze current issues in the Terragrunt project, such as when building an issue dashboard, performing issue triage, or when you need to stay updated with the latest project challenges and discussions. |
Setup
-
Install Deno:
-
Clone the repository:
git clone https://github.com/Excoriate/mcp-terragrunt-docs.git cd mcp-terragrunt-docs -
Set your GitHub token as an environment variable:
-
On Unix/macOS:
export GITHUB_TOKEN=ghp_xxx... # or GH_TOKEN or GITHUB_PERSONAL_ACCESS_TOKEN -
On Windows (cmd):
set GITHUB_TOKEN=ghp_xxx...
-
Note: You can also set the token in the
.envfile.
-
Run the MCP server:
# directly using deno deno run -A main.ts # Using the justfile just run # You can also debug it, and inspect it locally just inspect
The most straightforward method is to use it directly from JSR (Javascript Registry ❤️)
# export your github token
export GITHUB_TOKEN=ghp_xxx...
# run it
deno run -A jsr:@excoriate/[email protected]
Usage with Claude Desktop
To use this Deno-based MCP server with Claude Desktop, add the following to your claude_desktop_config.json:
Using Deno
{
"mcpServers": {
"terragrunt_docs": {
"command": "deno",
"args": [
"run",
"-A",
"main.ts"
],
"env": {
"GITHUB_TOKEN": "<YOUR_TOKEN>"
},
}
}
}
Using Docker
{
"mcpServers": {
"terragrunt_docs": {
"command": "docker",
"args": [
"run",
"-e", "GITHUB_TOKEN=<YOUR_TOKEN>", "mcp-terragrunt-docs"
],
"env": {
"GITHUB_TOKEN": "<YOUR_TOKEN>"
}
}
}
}
Using JSR
{
"mcpServers": {
"terragrunt_docs": {
"command": "deno",
"args": [
"run",
"-A",
"jsr:@excoriate/[email protected]"
],
"env": {
"GITHUB_TOKEN": "<YOUR_TOKEN>"
}
}
}
}
Build the Docker image
docker build -t mcp-terragrunt-docs .
Run the MCP server in Docker
docker run -it --rm \
-e GITHUB_TOKEN=ghp_xxx... \
mcp-terragrunt-docs
- Replace
ghp_xxx...with your GitHub Personal Access Token with appropriate permissions. - You can also use
GH_TOKENorGITHUB_PERSONAL_ACCESS_TOKENas the environment variable name. - If you want to use a local
.envfile, you can pass it with--env-file .env.
Contributing
See docs/CONTRIBUTING.md for detailed contribution guidelines, including setup, code style, PR process, and codebase structure reference.
Security
See SECURITY.md for the project's security policy, including how to report vulnerabilities and responsible disclosure guidelines.
License
This project is licensed under the MIT License.
Verwandte Server
Alpha Vantage MCP Server
SponsorAccess financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
MCP QEMU VM Control
Give your AI full computer access — safely. Let Claude (or any MCP-compatible LLM) see your screen, move the mouse, type on the keyboard, and run commands — all inside an isolated QEMU virtual machine. Perfect for AI-driven automation, testing, and computer-use experiments without risking your host system.
AltTester® AI Extension
MCP server for game test automation
Explorium API
Interact with the Explorium API to access external data for machine learning.
Just Prompt
A unified interface for various Large Language Model (LLM) providers, including OpenAI, Anthropic, Google Gemini, Groq, DeepSeek, and Ollama.
OpenAPI.city
Precise API context for AI agents, via MCP and REST.
MCP Chaos Rig
A local MCP server that breaks on demand. Test your client against auth failures, disappearing tools, flaky responses, and token expiry, all from a web UI.
Quantum Computation
Perform quantum computations using OpenAI and IBM Quantum APIs.
MCP Smart Contract Analyst
Analyzes smart contract source code on the Monad blockchain for functionality and security.
SR MCP
SR MCP-server: Access Swedish Radio open data. (Sveriges Radio)
PocketLantern
Blocker-aware decision layer for AI coding agents. Adds source-linked, time-sensitive blockers to AI technical choices — breaking changes, EOLs, lock-in, pricing shifts, and migration risk.