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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
OLLAMA_HOSTNoEndpoint of the local Ollama daemon.http://localhost:11434
OLLAMA_NUM_CTXNoContext window size allocated in local model memory.16384
OLLAMA_TIMEOUTNoRequest timeout in seconds for generation tasks.180
LOCAL_LLM_MODELNoPreferred model override (e.g. qwen2.5-coder:14b, deepseek-r1:14b). Auto-detected if not set.
OLLAMA_MCP_DEBUGNoSet to '1' to enable verbose diagnostic output to stderr.0
OLLAMA_TEMPERATURENoSampling temperature for code generation.0.2

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
local_draft_codeA

Generate initial code drafts, boilerplate, unit tests, or scaffolding locally via Ollama without consuming cloud tokens.

local_summarize_and_extractC

Compress massive files, logs, terminal traces, or documentation into high-density summaries before cloud reasoning.

local_chunked_summaryC

Map-reduce chunked summarization for massive files or logs that exceed single context limits.

local_extract_jsonB

Extract structured JSON from unstructured text, logs, or documentation according to a target schema description.

local_list_modelsA

List all models currently installed and available in the local Ollama instance.

local_prewarm_modelA

Pre-warm a local model into memory/VRAM with keep_alive=-1 so subsequent calls have zero cold-start delay.

local_map_reduce_fileB

Compress large files, traces, or logs using local Ollama Map-Reduce before ingesting into context.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

B3.2/5.0

Scored across 7 tools

Disambiguation2/5

The tools have significant overlap: local_summarize_and_extract, local_chunked_summary, and local_map_reduce_file all perform summarization/compression with only subtle differences. This can confuse an agent about which to use. Other tools are clearer, but the redundant trio lowers the score.

Naming Consistency3/5

All tools use a 'local_' prefix and snake_case, which is consistent, but the names are not fully uniform: 'summarize_and_extract' combines two actions while others use a single verb, and 'chunked_summary' vs 'map_reduce_file' are stylistic variations. The patterns are mostly consistent but not perfectly aligned.

Tool Count5/5

Seven tools is a reasonable, well-scoped number for a local Ollama helper. It covers core operations without being overwhelming, fitting comfortably within the typical 3-15 range.

Completeness4/5

The tools cover the main capabilities (code generation, summarization, extraction, model management, prewarming) well. However, the presence of three overlapping summarization tools suggests redundancy rather than a missing feature; the domain appears largely covered, with minor gaps like model downloading or inference not being addressed.

Maintenance

ActivityMaintained
ResponsivenessNo issues