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Glama
atsuki-sakai

Claude Code AI Collaboration MCP Server

by atsuki-sakai

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
NODE_ENVNoEnvironment mode (e.g., development, production).production
LOG_LEVELNoLogging level for the application.info
O3_API_KEYNoOptional O3 API key (defaults to OPENAI_API_KEY if not provided).
MCP_PROTOCOLNoTransport protocol to use for the server.stdio
OPENAI_API_KEYNoOptional OpenAI API key for GPT models integration.
DEEPSEEK_API_KEYYesDeepSeek API key required for the primary AI provider.
ANTHROPIC_API_KEYNoOptional Anthropic API key for Claude models support.
MCP_DISABLE_CACHINGNoWhether to disable the memory and Redis-compatible caching system.false
MCP_DISABLE_METRICSNoWhether to disable performance monitoring and OpenTelemetry metrics.false
MCP_DEFAULT_PROVIDERNoDefault AI provider to use for requests.deepseek

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": true
}
logging
{
  "level": "info"
}
resources
{
  "subscribe": true,
  "listChanged": true
}

Tools

Functions exposed to the LLM to take actions

NameDescription
collaborateC

Collaborate with multiple AI providers to solve complex problems

reviewC

Get comprehensive reviews of content from multiple AI perspectives

compareC

Compare multiple items using AI analysis across various dimensions

refineC

Iteratively refine and improve content through AI-powered analysis and enhancement

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription
Collaboration HistoryAccess to collaboration session history
Performance MetricsServer performance and usage metrics
Search IndexFull-text search capabilities

TDQS

B3/5.0

Scored across 4 tools

Disambiguation4/5

The tools have distinct primary purposes: collaboration, comparison, refinement, and review. However, there is some conceptual overlap between 'refine' (iterative improvement) and 'review' (comprehensive analysis), which could cause mild confusion in tool selection for certain tasks.

Naming Consistency5/5

All tool names follow a consistent verb-only pattern (collaborate, compare, refine, review), with no mixing of conventions or styles. This makes the tool set predictable and easy to navigate.

Tool Count3/5

With only 4 tools, the server feels slightly thin for its broad purpose of 'AI collaboration and analysis.' While each tool covers a distinct function, the scope suggests more granular operations (e.g., specific analysis types or collaboration modes) might be missing, making it borderline appropriate.

Completeness3/5

The tools cover high-level AI collaboration and analysis functions, but there are notable gaps in the surface. For example, there are no tools for managing collaboration sessions, saving/loading analyses, or handling specific data types, which limits workflow completeness for the domain.

Maintenance

ActivityInactive
ResponsivenessNo issues