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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
SERPER_API_KEYYesYour Serper API key for Google search (free at https://serper.dev)

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
{
  "listChanged": true
}
logging
{}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}

Tools

Functions exposed to the LLM to take actions

NameDescription
get_docsA

Fetch real-time, up-to-date documentation from the official docs site of a library.

Solves the core AI-engineer problem: LLMs have outdated training data. This tool fetches live content directly from official documentation websites, so you always get the latest API signatures, parameters, and examples.

search_docs_multiA

Search the same query across multiple libraries simultaneously.

Ideal for comparing how different frameworks handle the same concept:

  • "How does LangChain vs LlamaIndex implement RAG?"

  • "Compare asyncio support in FastAPI vs Django"

  • "Tool calling: OpenAI vs Anthropic vs Groq"

get_code_examplesA

Fetch working code examples for a specific library feature from official docs.

Unlike get_docs(), this tool specifically hunts for pages rich in code samples, extracting and formatting fenced code blocks for immediate use.

list_librariesA

List all 45+ supported documentation libraries, optionally filtered by category.

cache_statsA

Return current cache statistics for the LiveDocs MCP server.

Useful for understanding cache hit rates and diagnosing repeated query latency.

Returns: Cache statistics as formatted markdown.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A4.1/5.0

Scored across 5 tools

Disambiguation4/5

Each tool has a generally clear role: single-library docs, multi-library search, code examples, library listing, and cache stats. The only minor overlap is between get_docs and get_code_examples, but the descriptions explicitly differentiate them by focusing on prose/docs versus code-rich pages.

Naming Consistency4/5

Most tools follow a verb_noun pattern: get_docs, search_docs_multi, get_code_examples, list_libraries. cache_stats breaks the pattern by being noun_noun, and search_docs_multi's suffix is slightly irregular, but overall the naming is predictable and readable.

Tool Count5/5

Five tools is well-scoped for a documentation-fetching server. Each tool serves a distinct and useful purpose without redundancy or bloat, and the count feels appropriate for the narrow but valuable domain.

Completeness5/5

The tool surface covers the core documentation workflows: fetching live docs, searching across libraries, retrieving code examples, discovering supported libraries, and inspecting cache health. No obvious dead ends or missing critical operations for the stated purpose.

Maintenance

ActivityMaintained
ResponsivenessNo issues