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Glama

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
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
index_repoA

Ingest a repository and build the hybrid (dense + BM25) index.

Args: path: absolute path to the repo root to index.

statusA

Report index size and the active embedding backend.

search_codeA

Search the indexed codebase and return the top matching definitions.

Args: query: natural-language or keyword query. k: number of results. hybrid: True = dense + BM25 fusion; False = dense only. rerank: True = retrieve a wide pool and reorder with a cross-encoder (higher precision, slower; needs the [embeddings] extra).

get_contextA

Retrieve a ready-to-cite context bundle for answering a question.

Returns the source of the top matches (reranked by a cross-encoder when rerank=True, plus one-hop call-graph neighbors when expand_graph=True) with file:line citations, so the client model can answer grounded and cite spans.

impact_radiusA

Given a chunk id (from search results), list callers — the blast radius.

Args: chunk_id: id like 'pkg/mod.py::ClassA.method' (the qualname shown in results).

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

Disambiguation5/5

Each tool targets a distinct phase of the RAG workflow: indexing, status, searching, context retrieval, and impact analysis. search_code and get_context both retrieve code, but get_context explicitly adds citations and call-graph expansion, so they are clearly separated.

Naming Consistency4/5

All names use snake_case and follow a command-like style. However, status is a bare noun rather than verb_noun, and impact_radius is a noun phrase while others start with verbs (index, search, get). Minor deviations but overall predictable.

Tool Count5/5

Five tools is well-scoped for a code RAG server: one tool to build the index, one for health/size, one for basic search, one for context-rich retrieval, and one for dependency impact. No unnecessary tools.

Completeness4/5

The core lifecycle is covered: index creation, search, context extraction, and impact analysis. Missing explicit delete/re-index or list available repositories, but these are minor gaps for a focused RAG use case.

Maintenance

ActivitySlowing
ResponsivenessNo issues