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Enabling the MCP Server

The ai-rulez MCP (Model Context Protocol) server allows your AI assistant to programmatically and safely interact with your .ai-rulez/ configuration. Since V4 uses a file-based approach with inline MCP configuration, you define servers directly in config.toml, and the MCP server provides read, CRUD, validation, and generation tools for AI assistants.

You do not need to start the server manually. Your AI assistant will start it automatically based on the configuration you provide.


Configuration Examples

To enable the server, add one of the following snippets to your AI assistant's configuration file (e.g., Cursor's settings.json), or define it inline in .ai-rulez/config.toml.

This method ensures you are always using the latest version of ai-rulez without needing to install it globally.

{
  "mcp_servers": {
    "ai-rulez": {
      "command": "npx",
      "args": ["-y", "ai-rulez@latest", "mcp"]
    }
  }
}

This method uses uvx to run ai-rulez in an ephemeral environment.

{
  "mcp_servers": {
    "ai-rulez": {
      "command": "uvx",
      "args": ["ai-rulez", "mcp"]
    }
  }
}

Using a Local Go Installation

If you have installed ai-rulez locally with go install.

{
  "mcp_servers": {
    "ai-rulez": {
      "command": "ai-rulez",
      "args": ["mcp"]
    }
  }
}

V4 supports defining MCP servers directly in your .ai-rulez/config.toml:

[[mcp_servers]]
name = "ai-rulez"
command = "npx"
args = ["-y", "ai-rulez@latest", "mcp"]

[[mcp_servers]]
name = "grafana"
command = "uvx"
args = ["mcp-grafana"]
env = { GRAFANA_URL = "http://localhost:3000", GRAFANA_SERVICE_ACCOUNT_TOKEN = "${GRAFANA_SERVICE_ACCOUNT_TOKEN}" }

MCP env values may contain ${VAR} placeholders. ai-rulez generate resolves them from repeated --env KEY=VALUE flags, process environment variables, then dotenv files. Placeholder names must match [A-Za-z_][A-Za-z0-9_]*. By default, .env is loaded from the generation base directory. If any --env-file PATH flags are supplied, the default .env is not loaded; multiple files are merged in flag order, with later files winning. Generation fails if a placeholder cannot be resolved.

Generated MCP config files contain resolved values. If a value came from a placeholder, or if an env key contains TOKEN, SECRET, PASSWORD, KEY, or CREDENTIAL, generation fails before writing unless .mcp.json, .claude/settings.json, .gemini/settings.json, .agents/settings.json, or a scoped variant is gitignored or covered by planned --gitignore patterns. Secret-bearing values are redacted before source-hash calculation, not from generated MCP config files.

Set enabled = false on an inline [[mcp_servers]] entry to skip it in generated MCP outputs.


Server Capabilities

When enabled, the MCP server provides your AI assistant with access to your configuration and CRUD operations. The server supports:

  • Read Configuration: Inspect rules, context, skills, profiles, and presets
  • Generate Outputs: Programmatically trigger generation of tool-specific files
  • Validate Configuration: Check configuration validity and report errors
  • CRUD Operations: Create, read, update, and delete domains, rules, context, skills, includes, and profiles

The MCP server enables AI assistants to:

  1. Understand your setup by reading configuration and content files
  2. Modify configuration programmatically via CRUD tools
  3. Generate outputs after changes
  4. Validate changes before committing

This approach ensures your configuration remains auditable and version-controlled, while allowing AI assistants to help you manage it efficiently.

Typical Workflow

With Your Editor

  1. Edit files directly in .ai-rulez/:
# Edit rules, context, skills, or config.toml
vim .ai-rulez/rules/code-quality.md
  1. Use MCP server (via AI assistant) to generate:
ai-rulez generate
  1. Commit changes:
git add .ai-rulez/ CLAUDE.md .cursor/
git commit -m "docs: update AI guidelines"

With Claude CLI

If using the Claude CLI with the ai-rulez MCP server, you can ask Claude to help:

  • "Review my .ai-rulez/ configuration and suggest improvements"
  • "Generate outputs for my new rules"
  • "Validate that my profiles are correct"
  • "Create a new backend domain and add database rules"
  • "Add an include from our shared rules repository"

The server provides Claude with access to read and modify your configuration, while you maintain full control over final decisions.


MCP Tools Reference

The ai-rulez MCP server exposes 35 tools for programmatic configuration management. These tools allow AI assistants to initialize projects, generate outputs, validate configuration, inspect builtins, and create, read, update, and delete configuration elements.

Project and Utility Tools

generate_outputs

Generate output files from the current configuration.

Parameters:

  • config_file (optional, string): Path to the root configuration file
  • config_dir (optional, string): Configuration directory name (default: .ai-rulez)
  • dry_run (optional, boolean): Preview changes without writing files
  • recursive (optional, boolean): Generate for all subdirectories containing .ai-rulez/
  • working_directory (optional, string): Directory to operate in

validate_config

Validate the configuration file, including all includes.

Parameters:

  • config_file (optional, string): Path to the root configuration file
  • config_dir (optional, string): Configuration directory name (default: .ai-rulez)
  • working_directory (optional, string): Directory to operate in

init_project

Initialize a new ai-rulez project in the current directory.

Parameters:

  • project_name (optional, string): Project name
  • providers (optional, array): Providers to enable, such as claude or cursor
  • with_agents (optional, boolean): Include sample agent configurations
  • all_providers (optional, boolean): Enable all supported providers
  • popular_providers (optional, boolean): Enable the curated popular provider set
  • working_directory (optional, string): Directory to operate in

get_version

Return the ai-rulez version.

Parameters: (none)

show_builtin

Show the full content of a builtin domain.

Parameters:

  • name (required, string): Builtin domain name, such as security, rust, or typescript

Domain Tools

create_domain

Create a new domain with subdirectories for rules, context, and skills.

Parameters:

  • name (required, string): Domain name (alphanumeric and underscores, 1-50 characters)
  • description (optional, string): Description of the domain

Response:

{
  "success": true,
  "operation": "create_domain",
  "name": "backend",
  "path": ".ai-rulez/domains/backend",
  "message": "Domain created successfully"
}

Example:

Create a domain called "backend" for backend services

delete_domain

Delete a domain and all its contents.

Parameters:

  • name (required, string): Domain name to delete

Response:

{
  "success": true,
  "operation": "delete_domain",
  "name": "backend",
  "message": "Domain deleted successfully"
}

list_domains

List all domains in the .ai-rulez/ directory.

Parameters: (none)

Response:

{
  "success": true,
  "operation": "list_domains",
  "domains": [
    {
      "name": "backend",
      "path": ".ai-rulez/domains/backend",
      "rulesCount": 3,
      "contextCount": 2,
      "skillsCount": 1
    }
  ],
  "count": 1
}

Rule Tools

create_rule

Create a new rule file with optional YAML frontmatter.

Parameters:

  • name (required, string): Rule filename without .md extension
  • content (optional, string): Markdown content with optional YAML frontmatter
  • domain (optional, string): Domain name (if not specified, creates in root)
  • priority (optional, string): Priority level - critical, high, medium, low. Default: medium
  • targets (optional, array): Target providers (e.g., ["claude", "cursor"])

Response:

{
  "success": true,
  "operation": "create_rule",
  "path": ".ai-rulez/rules/code-quality.md",
  "name": "code-quality",
  "domain": null,
  "message": "Rule created successfully"
}

update_rule

Update an existing rule file.

Parameters:

  • name (required, string): Rule filename without .md extension
  • content (required, string): New markdown content
  • domain (optional, string): Domain name
  • priority (optional, string): Priority level
  • targets (optional, array): Target providers

Response: Same as create_rule

read_rule

Read a rule file.

Parameters:

  • name (required, string): Rule filename without .md extension
  • domain (optional, string): Domain name
  • working_directory (optional, string): Directory to operate in

delete_rule

Delete a rule file.

Parameters:

  • name (required, string): Rule filename without .md extension
  • domain (optional, string): Domain name

Response:

{
  "success": true,
  "operation": "delete_rule",
  "name": "code-quality",
  "domain": null,
  "message": "Rule deleted successfully"
}

list_rules

List all rules in the root or a specific domain.

Parameters:

  • domain (optional, string): Domain name (lists root rules if not specified)

Response:

{
  "success": true,
  "operation": "list_rules",
  "domain": null,
  "rules": [
    {
      "name": "code-quality",
      "path": ".ai-rulez/rules/code-quality.md",
      "priority": "high",
      "targets": ["claude", "cursor"]
    }
  ],
  "count": 1
}

Context Tools

create_context

Create a new context file (documentation/reference material).

Parameters:

  • name (required, string): Context filename without .md extension
  • content (optional, string): Markdown content with optional YAML frontmatter
  • domain (optional, string): Domain name
  • priority (optional, string): Priority level
  • targets (optional, array): Target providers

Response: Similar to create_rule

update_context

Update an existing context file.

Parameters: Same as create_context, with content as required

Response: Similar to create_rule

read_context

Read a context file.

Parameters:

  • name (required, string): Context filename without .md extension
  • domain (optional, string): Domain name
  • working_directory (optional, string): Directory to operate in

delete_context

Delete a context file.

Parameters:

  • name (required, string): Context filename without .md extension
  • domain (optional, string): Domain name

Response: Similar to delete_rule

list_context

List all context files in the root or a specific domain.

Parameters:

  • domain (optional, string): Domain name

Response: Similar to list_rules, with "context" key instead of "rules"

Skill Tools

create_skill

Create a new skill file (AI prompt/expert definition).

Parameters:

  • name (required, string): Skill filename without .md extension
  • content (optional, string): Markdown content with optional YAML frontmatter
  • domain (optional, string): Domain name
  • priority (optional, string): Priority level
  • targets (optional, array): Target providers

Response: Similar to create_rule

update_skill

Update an existing skill file.

Parameters: Same as create_skill, with content as required

Response: Similar to create_rule

read_skill

Read a skill file.

Parameters:

  • name (required, string): Skill filename without .md extension
  • domain (optional, string): Domain name
  • working_directory (optional, string): Directory to operate in

delete_skill

Delete a skill file.

Parameters:

  • name (required, string): Skill filename without .md extension
  • domain (optional, string): Domain name

Response: Similar to delete_rule

list_skills

List all skill files in the root or a specific domain.

Parameters:

  • domain (optional, string): Domain name

Response: Similar to list_rules, with "skills" key instead of "rules"

Include Tools

add_include

Add a new include source (git URL or local path) to the configuration.

Parameters:

  • name (required, string): Include name (unique identifier)
  • source (required, string): Git URL (https://github.com/org/repo) or local path (./packages/shared)
  • path (optional, string): Path within git repository where .ai-rulez/ content is located
  • ref (optional, string): Git reference - branch, tag, or commit hash (git sources only). Default: main
  • include (optional, array): Content types to include - rules, context, skills, mcp
  • merge_strategy (optional, string): Merge strategy - default, override, append
  • install_to (optional, string): Installation target path in .ai-rulez/

Response:

{
  "success": true,
  "operation": "add_include",
  "name": "corporate-rules",
  "source": "https://github.com/myorg/shared-rules",
  "message": "Include added successfully"
}

remove_include

Remove an include source from the configuration.

Parameters:

  • name (required, string): Include name to remove

Response:

{
  "success": true,
  "operation": "remove_include",
  "name": "corporate-rules",
  "message": "Include removed successfully"
}

list_includes

List all include sources in the configuration.

Parameters: (none)

Response:

{
  "success": true,
  "operation": "list_includes",
  "includes": [
    {
      "name": "corporate-rules",
      "source": "https://github.com/myorg/shared-rules",
      "ref": "main",
      "path": ".ai-rulez",
      "mergeStrategy": "default"
    }
  ],
  "count": 1
}

Installed Skill Tools

install_skill

Install a named skill from a git repository or local path.

Parameters:

  • name (required, string): Skill name (unique identifier)
  • source (required, string): Git URL or local filesystem path
  • path (optional, string): Path within repo to skill directory (defaults to skills/<name>)
  • ref (optional, string): Git reference (branch, tag, commit)

Response:

{
  "success": true,
  "operation": "install_skill",
  "name": "kreuzberg",
  "source": "https://github.com/kreuzberg-dev/kreuzberg",
  "message": "Skill installed successfully"
}

uninstall_skill

Remove an installed skill from the configuration.

Parameters:

  • name (required, string): Skill name to remove

Response:

{
  "success": true,
  "operation": "uninstall_skill",
  "name": "kreuzberg",
  "message": "Skill uninstalled successfully"
}

list_installed_skills

List all installed skills.

Parameters: None

Response:

{
  "success": true,
  "operation": "list_installed_skills",
  "installed_skills": [
    {
      "Name": "kreuzberg",
      "Source": "https://github.com/kreuzberg-dev/kreuzberg",
      "Path": "skills/kreuzberg",
      "Ref": "",
      "Type": "git"
    }
  ],
  "count": 1
}

Config Tools

read_config

Read the current project configuration as structured JSON.

Parameters:

  • working_directory (optional, string): Directory to operate in

update_config

Update supported project configuration fields.

Parameters:

  • name (optional, string): Project name
  • description (optional, string): Project description
  • builtins (optional, array): Builtin names to enable
  • gitignore (optional, boolean): Whether generation updates .gitignore
  • default_effort (optional, string): Default reasoning effort
  • default_effort_by_preset (optional, object): Per-preset reasoning effort overrides
  • working_directory (optional, string): Directory to operate in

Profile Tools

add_profile

Create a new profile with a set of domains.

Parameters:

  • name (required, string): Profile name (unique identifier)
  • domains (required, array): List of domain names to include in the profile

Response:

{
  "success": true,
  "operation": "add_profile",
  "name": "full",
  "domains": ["backend", "frontend", "qa"],
  "message": "Profile added successfully"
}

remove_profile

Remove a profile from the configuration.

Parameters:

  • name (required, string): Profile name to remove

Response:

{
  "success": true,
  "operation": "remove_profile",
  "name": "staging",
  "message": "Profile removed successfully"
}

set_default_profile

Set a profile as the default for generation.

Parameters:

  • name (required, string): Profile name to set as default

Response:

{
  "success": true,
  "operation": "set_default_profile",
  "name": "full",
  "message": "Default profile set successfully"
}

list_profiles

List all profiles in the configuration.

Parameters: (none)

Response:

{
  "success": true,
  "operation": "list_profiles",
  "profiles": [
    {
      "name": "full",
      "domains": ["backend", "frontend", "qa"],
      "isDefault": true
    },
    {
      "name": "backend",
      "domains": ["backend", "qa"],
      "isDefault": false
    }
  ],
  "count": 2
}

Common MCP Workflows

Creating a Domain with Rules

User: "Create a backend domain and add a database standards rule"

MCP Tool Sequence:
1. create_domain(name: "backend", description: "Backend services")
2. create_rule(name: "database-standards", domain: "backend", priority: "high", content: "...")
3. generate_outputs() - regenerate configurations

Adding an External Include

User: "Add our corporate rules from GitHub"

MCP Tool Sequence:
1. add_include(name: "corporate", source: "https://github.com/myorg/rules", ref: "main")
2. validate_config() - check if include is valid
3. generate_outputs() - regenerate with included content

Setting Up Team Profiles

User: "Create backend and frontend profiles for our team separation"

MCP Tool Sequence:
1. create_domain(name: "backend")
2. create_domain(name: "frontend")
3. add_profile(name: "backend", domains: ["backend"])
4. add_profile(name: "frontend", domains: ["frontend"])
5. set_default_profile(name: "backend")
6. generate_outputs()

Bulk Content Creation

User: "Add security rules to the backend domain"

MCP Tool Sequence:
1. create_rule(name: "authentication", domain: "backend", content: "...")
2. create_rule(name: "encryption", domain: "backend", content: "...")
3. create_context(name: "security-architecture", domain: "backend", content: "...")
4. validate_config()
5. generate_outputs()