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Glama
LoganZechella

MCP DeepWiki Server

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

Server capabilities have not been inspected yet.

Tools

Functions exposed to the LLM to take actions

NameDescription
deepwiki_fetchC

Retrieves GitHub repository documentation from DeepWiki with enhanced content organization and filtering capabilities.

deepwiki_summarizeB

Generates AI-powered summaries of GitHub repository documentation with different focus types (overview, technical, quickstart, api).

deepwiki_searchC

Search for GitHub repositories with documentation available on DeepWiki. Supports filtering by programming language and topics.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

B3.4/5.0

Scored across 3 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: fetch retrieves documentation, search finds repositories, and summarize generates AI summaries. There is no overlap in functionality, making tool selection straightforward for an agent.

Naming Consistency5/5

All tools follow a consistent 'deepwiki_' prefix with descriptive action suffixes (fetch, search, summarize). This uniform naming pattern enhances predictability and readability.

Tool Count4/5

Three tools is appropriate for a focused documentation server, covering core operations. It might be slightly lean, but each tool serves a distinct, valuable purpose without redundancy.

Completeness4/5

The tools cover key workflows: searching for repositories, fetching documentation, and summarizing content. Minor gaps may exist, such as advanced filtering or update operations, but the core domain is well-covered for typical agent tasks.