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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
OLLAMA_HOSTNoOllama endpointhttp://localhost:11434
SQLITE_RAG_DBNoIndex database path~/.local/share/sqlite-rag-mcp/index.db
SQLITE_RAG_EMBED_MODELNoEmbedding modelnomic-embed-text
SQLITE_RAG_CHUNK_TOKENSNoChunk size (approx. tokens)800
SQLITE_RAG_CHUNK_OVERLAPNoChunk overlap (approx. tokens)100

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_documentsA

Index text/markdown files from a directory into the local SQLite index.

Args: path: Directory to index (absolute or ~-expanded). glob: Glob pattern relative to the directory (default '/*.md'). Use e.g. '/.txt' or '**/' for other text files.

searchA

Search the indexed documents.

Args: query: Natural-language query or keywords. k: Number of results to return (1-50, default 8). mode: 'hybrid' (RRF fusion of semantic + lexical, default), 'semantic' (vector KNN only), or 'lexical' (FTS5 BM25 only). If Ollama is offline, hybrid/semantic fall back to lexical and a warning is included in the response.

get_chunkA

Fetch the full text and source of a chunk returned by search.

statsB

Index statistics: document/chunk/embedding counts and configuration.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A3.8/5.0

Scored across 4 tools

Disambiguation5/5

Each tool has a unique, clearly distinct purpose: indexing documents, searching, fetching chunk details, and statistics. No overlap or ambiguity.

Naming Consistency4/5

Most names follow a verb_noun pattern (get_chunk, index_documents), but 'search' and 'stats' are single words without an object, introducing minor inconsistency.

Tool Count5/5

4 tools is appropriate for a focused RAG server: indexing, querying with retrieval, chunk access, and monitoring. Each tool serves a necessary role.

Completeness4/5

Covers the core RAG workflow (index, search, retrieve). Missing a delete or clear index function, but not a major gap for typical usage.

Maintenance

ActivityStale
ResponsivenessNo issues