Skip to main content
Glama
lfdantoni

Personal Code Skills MCP Server

by lfdantoni
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Remote

my-personal-code-mcp

An MCP (Model Context Protocol) server that provides AI assistants with access to best practice skills stored as markdown files in a GitHub repository.

Features

  • list_skills: Returns a list of all available skill names from the configured repository

  • get_skill: Retrieves the content of a specific skill by name

Related MCP server: GitHub MCP Server

Installation

# Clone the repository
git clone https://github.com/lfdantoni/my-personal-code-mcp.git
cd my-personal-code-mcp

# Install dependencies
npm install

# Build
npm run build

Configuration

Environment Variables

Variable

Description

Required

SKILLS_REPO_OWNER

GitHub repository owner (username or organization)

Yes

SKILLS_REPO_NAME

GitHub repository name

Yes

SKILLS_PATH

Subdirectory containing skill files (default: root)

No

GITHUB_TOKEN

GitHub personal access token (required for private repos)

No

Skills Repository Structure

Your skills repository should contain markdown files (.md) with best practices:

your-skills-repo/
├── typescript-best-practices.md
├── react-patterns.md
├── testing-guidelines.md
└── ...

Or with a subdirectory:

your-skills-repo/
└── skills/
    ├── typescript-best-practices.md
    ├── react-patterns.md
    └── ...

MCP Client Configuration

Cursor

Add the following to your Cursor MCP settings file (~/.cursor/mcp.json or via Settings > MCP):

{
  "mcpServers": {
    "my-personal-code-mcp": {
      "command": "node",
      "args": ["C:/path/to/my-personal-code-mcp/dist/index.js"],
      "env": {
        "SKILLS_REPO_OWNER": "your-github-username",
        "SKILLS_REPO_NAME": "your-skills-repo",
        "SKILLS_PATH": "",
        "GITHUB_TOKEN": "ghp_your_token_here"
      }
    }
  }
}

Claude Desktop

Add the following to your Claude Desktop configuration file:

Windows: %APPDATA%\Claude\claude_desktop_config.json macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "my-personal-code-mcp": {
      "command": "node",
      "args": ["C:/path/to/my-personal-code-mcp/dist/index.js"],
      "env": {
        "SKILLS_REPO_OWNER": "your-github-username",
        "SKILLS_REPO_NAME": "your-skills-repo",
        "SKILLS_PATH": "",
        "GITHUB_TOKEN": "ghp_your_token_here"
      }
    }
  }
}

Claude Code CLI

Add to your Claude Code settings (~/.claude/settings.json):

{
  "mcpServers": {
    "my-personal-code-mcp": {
      "command": "node",
      "args": ["/path/to/my-personal-code-mcp/dist/index.js"],
      "env": {
        "SKILLS_REPO_OWNER": "your-github-username",
        "SKILLS_REPO_NAME": "your-skills-repo"
      }
    }
  }
}

Available Tools

list_skills

Returns a list of all available skill names.

Input: None

Output:

{
  "skills": ["typescript-best-practices", "react-patterns", "testing-guidelines"]
}

get_skill

Returns the content of a specific skill.

Input:

{
  "skill_name": "typescript-best-practices"
}

Output: The markdown content of the skill file.

Development

# Build
npm run build

# Watch mode
npm run dev

# Run the server
npm start

License

ISC

Available Tools

2 tools
get_skillC

Returns the content of a specific best practice skill

ParametersJSON Schema
NameRequiredDescriptionDefault
skill_nameYesThe name of the skill to retrieve

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a read operation ('Returns'), but doesn't cover aspects like error handling, authentication needs, rate limits, or what 'content' entails. This leaves significant gaps for a tool with no annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It's appropriately sized and front-loaded with the core purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'content' includes (e.g., text, metadata, examples), potential errors, or how it relates to the sibling tool. For a tool with no structured support, more context is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, with the parameter 'skill_name' fully documented in the schema. The description doesn't add any additional meaning beyond what the schema provides (e.g., format examples or constraints), so it meets the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Returns') and resource ('content of a specific best practice skill'), making the purpose understandable. However, it doesn't explicitly differentiate from the sibling tool 'list_skills' (which presumably lists multiple skills rather than retrieving content of a specific one), preventing a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention the sibling tool 'list_skills' or any other context for selection, leaving usage decisions unclear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

list_skillsB

Returns a list of all available best practice skills

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

B3/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool returns a list but doesn't mention any behavioral traits such as pagination, rate limits, authentication requirements, or potential side effects. This is inadequate for a tool with zero annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and appropriately sized for a simple tool, though it could be slightly more structured to include usage context.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the returned list contains (e.g., skill names, IDs, metadata), how it's formatted, or any limitations. For a tool with no structured data beyond the input schema, more context is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters, and the schema description coverage is 100%, so there's no need for parameter details in the description. The baseline for this scenario is 4, as the description appropriately avoids redundant information about parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Returns') and resource ('list of all available best practice skills'), making the purpose understandable. However, it doesn't differentiate from its sibling 'get_skill' (which presumably retrieves a single skill), so it doesn't reach the highest score of 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus its sibling 'get_skill' or any alternatives. It lacks context about use cases, prerequisites, or exclusions, leaving the agent without direction on tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 2 tool updatesv1.0.0
    • First observedget_skill
    • First observedlist_skills
Install Server
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

B3.1/5.0
Disambiguation5/5

The two tools have clearly distinct purposes: get_skill retrieves detailed content for a specific skill, while list_skills provides an overview of all available skills. There is no overlap or ambiguity between them, making it easy for an agent to select the correct tool based on the task.

Naming Consistency5/5

Both tools follow a consistent verb_noun pattern (get_skill and list_skills), using snake_case throughout. The naming is predictable and readable, with no deviations or mixed conventions.

Tool Count2/5

With only 2 tools, the server feels thin for a 'Personal Code Skills' domain that implies management of skills. While basic read operations are covered, the lack of create, update, or delete tools suggests an incomplete surface for skill management, making the count too low for the apparent scope.

Completeness2/5

The server only provides read operations (get and list), with no ability to create, update, or delete skills. This is a significant gap for a skills management domain, as agents cannot modify or add new skills, leading to potential dead ends in workflows that require full lifecycle management.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Connectors

Related MCP Servers

Appeared in Searches

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/lfdantoni/my-personal-code-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server