mcp-guide
Delivers organized project guidelines and context to GitHub Copilot through MCP, ensuring consistent information for AI-powered coding assistance.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mcp-guideget the development workflow guide"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
mcp-guide
Structured content delivery for AI agents via Model Context Protocol
mcp-guide is an MCP server that provides AI agents with organised access to project guidelines, documentation, and context. It helps agents understand your project's standards, follow development workflows, and access relevant information through a flexible content management system.
Key Features
Content Management - Organise documents, instructions and prompts by category and collection
Template Support - Dynamic content with Mustache/Chevron templates
Multiple Transports - STDIO, HTTP, and HTTPS modes
Feature Flags - Project-specific and global configuration
Workflow Management - Structured development phase tracking
Profile System - Pre-configured setups for common scenarios
Docker Support - Containerised deployment with SSL
OpenSpec Integration - Spec-driven development workflow
Quick Start
mcp-guide is run using your AI Agent's MCP configuration, and not usually run directly, at least in stdio transport mode. In stdio mode, standard input and output are used to communicate with the MCP so the agent needs to control both in order to operate. In http mode, however, the server provides web server (http) transport, and this may be started in standalone mode, not necessarily by the agent directly (although typically it does).
The configurations below detail configuration with some cli agents, but almost all of them will be similar.
Configure with AI Agents
JSON configuration
These blocks can be used as is and inserted into the agent's configuration. The stdio mode is a straightforward configuration, although it requires the uv tool to be installed.
Stdio
{
"mcpServers": {
"mcp-guide": {
"command": "uvx",
"args": ["mcp-guide"]
}
}
}If the "mcpServers" block already exists, add the "mcp-guide" block at the end, ensuring that the previously last item, if any, has a terminating comma.
Kiro-CLI
Add the above JSON block to ~/.kiro/settings/mcp.json.
Claude Code
Add the above JSON block to ~/.claude/settings.json.
GitHub Copilot CLI
Add this JSON block to ~/.config/.copilot/mcp.json.
Other clients will offer similar configuration, some also
See the Installation Guide for more detail in use with various clients, use with docker and using the http/sse transport mode.
Content Organisation
mcp-guide organises content using frontmatter (optional YAML metadata at the start of documents) to define document properties and behaviour.
Content is classified into three types via the type: field in frontmatter:
user/information - Content displayed to users
agent/information - Context for AI agents
agent/instruction - Directives for agent behaviour
Content is organised using categories (file patterns and directories) and collections (groups of categories). Collections act as "macros" to provide targeted context for specific tasks or purposes.
See Content Management for details.
Feature Flags
Feature flags control behaviour, capabilities and special features and may be set globally or per project:
workflow - Enable workflow phase tracking
openspec - Enable OpenSpec integration
content-style - Output format (None, plain, mime)
See Feature Flags for more information.
Documentation
Documentation Index - Documentation overview
Getting Started - First-time setup and basic concepts
Changelog - Release notes and version history
Links
Documentation: deeprave.github.io/mcp-guide
Issues: GitHub Issues
MCP Protocol: modelcontextprotocol.io
License
MIT License - See LICENSE.md for details.
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