Skip to main content
Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
RAG_DIMNoEmbedding dimension. Default: 384384
RAG_HOMENoData dir (index, sources.yaml). Default: ~/.shelfmark~/.shelfmark
RAG_QLOGNoLocal query telemetry (powers report.py). Default: offoff
RAG_MODELNoEmbedding model. Default: e5-smalle5-small
RAG_BM25_WEIGHTNoBM25 weight; >1 favors lexical match. Default: 1.51.5
RAG_CODE_RERANKNobge-reranker-v2-m3 for code scopes (+4.9pp, ~2.2GB). Default: offoff
RAG_RERANK_AUTONoRerank weak/ambiguous queries. Default: onon
RAG_KNOWLEDGE_SCOPENoConfigures cross-project search scope for durable knowledge.

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
rag_queryA

Hybrid semantic + BM25 search over the user's configured corpus: notes, docs, repo docs + README + CHANGELOG, recent git commits, session transcripts, and source code (TS/JS/Python/Shell) from the configured repos. Returns top-K chunks with path:line + symbol + repo citations. Auto-scopes to the current repo when cwd is inside one — pass scope_repos=['all'] to disable. Use instead of grep for fuzzy or cross-file recall.

search_knowledgeA

Semantic search over the knowledge layer — durable notes and decisions: memory notes, ADRs, plans, session handoffs, and standards (NOT source code or git commits). Cross-project by design (searches all repos, no cwd auto-scoping). Use for 'what did we decide / is there a note about X / did we hit this before'. For source-code or git-commit recall, use rag_query instead.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

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/LucasSantana-Dev/shelfmark'

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