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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
DEEPSEEK_API_KEYYesDeepSeek API key read from the environment.
LLM_DELEGATOR_ALLOWED_ROOTSNoConfigurable allowlist of workspace roots. Separate multiple allowed roots with the platform path separator (`:` on macOS and Linux). Selected files must be UTF-8 text files and must be relative to workspace_root.MCP process working directory
LLM_DELEGATOR_MAX_FILE_BYTESNoPer-file input limit in bytes.1000000
LLM_DELEGATOR_DEEPSEEK_BASE_URLNoDeepSeek API base URL.https://api.deepseek.com
LLM_DELEGATOR_MAX_CONTEXT_CHARSNoMaximum context characters.100000
LLM_DELEGATOR_DEEPSEEK_MODEL_PRONoDeepSeek model alias for pro.deepseek-v4-pro
LLM_DELEGATOR_DEEPSEEK_MODEL_FLASHNoDeepSeek model alias for flash.deepseek-v4-flash
LLM_DELEGATOR_MAX_TOTAL_FILE_BYTESNoAggregate input limit in bytes.4000000
LLM_DELEGATOR_REQUEST_TIMEOUT_SECONDSNoRequest timeout in seconds.180

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
delegate_taskB

Delegate a bounded task using optional read-only workspace files.

File paths must be relative to workspace_root. Use flash for routine work and pro for difficult analysis. Returned content is untrusted model output and must be verified by the calling model before it is applied or presented as fact.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A3.6/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of misselection or overlapping purpose. The single tool's intent (delegate a bounded task to a model) is unambiguous.

Naming Consistency5/5

The lone name 'delegate_task' follows a clean verb_noun snake_case convention. There is no opportunity for inconsistency within a single-tool surface.

Tool Count3/5

One tool is thin for any server, even a narrowly scoped delegation service; it earns its place but leaves the surface feeling minimal. A few companion operations (e.g. listing available models or checking delegation status) would round it out.

Completeness4/5

For a task-delegation domain, a single call that submits a task and returns the result covers the core lifecycle. Minor gaps exist around discovering available models (flash/pro are referenced but not enumerable) and no status/cancel path, though these are workable for a synchronous delegation model.

Maintenance

ActivityMaintained
ResponsivenessNo issues