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skainguyen1412

MCP Codebase Mentor

by skainguyen1412
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
init_codebaseA

Initialize and index a codebase for AI mentoring. This tool:

  • Crawls the directory structure (respecting .gitignore)

  • Analyzes each file to extract summaries, imports, and exports

  • Builds a manifest with file metadata and dependency graph

  • Creates a vector index for semantic search

Run this before using generate_tutorial or search_codebase.

generate_tutorialA

Generate a comprehensive tutorial/learning guide for a codebase. Creates a "Zero to Hero" tutorial with:

  • Project overview and architecture

  • Mermaid.js dependency diagrams

  • Structured learning path (chapters)

  • Key insights and patterns

Requires init_codebase to be run first.

search_codebaseA

Perform semantic search across a codebase. Uses vector embeddings to find relevant code sections based on natural language queries.

Returns:

  • Matching code snippets with file paths and line numbers

  • Relevance scores

  • File context and summaries

Requires init_codebase to be run first.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.2/5.0

Scored across 3 tools

Disambiguation5/5

Each tool has a distinct responsibility: init_codebase prepares the index, search_codebase queries it, and generate_tutorial creates learning content from the indexed data. There is no overlap in purpose or behavior.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern: init_codebase, generate_tutorial, search_codebase. The naming is uniform, predictable, and clearly indicates each tool's action.

Tool Count5/5

With only 3 tools, the server is tightly scoped to its purpose of codebase mentoring. Each tool is essential to the workflow, and the small count is appropriate for a focused toolset.

Completeness5/5

The toolset covers the full lifecycle: initialization, semantic search, and tutorial generation. For the stated domain, there are no obvious missing operations that would leave an agent stuck.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources