Skip to main content
Glama

athena-mcp

ヘルメスが立ち往生したとき、アテナに尋ねる。

ツールを使用するエージェントに推論の相棒を提供するMCPサーバーです。ツールは think の1つだけ。副作用はありません。アテナ自身はツールを持たず、ただ推論するだけです。

メインのエージェント(ヘルメス、Claude Code、Cursor、その他MCP対応クライアント)が、微妙なバグ、アーキテクチャの判断、批判が必要な計画など、難しい問題に直面したとき、think を呼び出すことで、簡潔で論理的な回答を得ることができます。エージェントは主導権を維持したまま、デフォルトのモデルでは手に負えない難問に直面したときに、静かなコンサルタントであるアテナに頼ることができます。

Codebuffのthinkerエージェントから着想を得ています。Codebuffでは、コンテキストを収集した後にツールを持たない thinker-gpt を起動し、その唯一の仕事として「深く考え、簡潔な回答を返す」ことを行っています。

なぜ分離するのか?

ほとんどのエージェントは、すべてを1つのモデルで実行します。そのモデルは妥協の産物であり、何百ものツール呼び出しには高速で安価ですが、そのほとんどに対しては十分な賢さしかありません。しかし、本当に立ち往生したときには、別のモデル(推論能力の高いClaude Opus、GPT-5、Gemini Pro、DeepSeek R1など)が必要になります。その際、タスクの残りの部分の制御権を手放す必要はありません。それがアテナの役割です。

Available Tools

1 tool
thinkA

Ask Athena to think. Delegates deep reasoning to a stronger model when you hit a hard problem — architecture decisions, subtle bugs, plan critique, tricky logic. Athena has NO tools; she only reasons and returns a concise response. You must gather relevant context yourself and pass it in via the context arg. Does not modify files, run commands, or access the network beyond the reasoning call.

NameRequiredDescriptionDefault
promptYesThe problem to think about. Can be brief — Athena will reason about it carefully. Example: "Is this race condition in the claim() function real, and if so what's the minimal fix?"
contextNoOptional. Relevant code, conversation excerpts, error messages, or other material Athena needs. Athena cannot read files, so anything it needs to see must be pasted here.
effortNoOptional reasoning effort override. Defaults to high. Use "high" for the hardest problems, "low" for quick sanity checks.
modelNoOptional model override. Defaults to anthropic/claude-opus-4.6. Accepted values for current backend (openrouter): anthropic/claude-opus-4.6, openai/gpt-5.4, google/gemini-3.1-pro-preview, deepseek/deepseek-r1.

TDQS

A4.4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key traits: Athena 'only reasons and returns a concise response,' has 'NO tools,' and 'Does not modify files, run commands, or access the network beyond the reasoning call.' It also notes that 'You must gather relevant context yourself.' However, it lacks details on rate limits, authentication needs, or error handling, which would elevate it to a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded, with the first sentence stating the core purpose. Each subsequent sentence adds critical information without redundancy: usage context, limitations, and parameter guidance. There is zero waste, and the structure flows logically from general to specific details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (reasoning delegation with no output schema) and lack of annotations, the description is mostly complete. It covers purpose, usage, behavioral traits, and some parameter context. However, without an output schema, it doesn't detail return values or error formats, which is a minor gap. For a tool with no annotations and no output schema, this is strong but not perfect.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all four parameters thoroughly. The description adds minimal value beyond the schema, mentioning the 'context' arg briefly ('You must gather relevant context yourself and pass it in via the `context` arg.') but not explaining other parameters. This meets the baseline of 3 for high schema coverage, as the description doesn't significantly enhance parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Ask Athena to think. Delegates deep reasoning to a stronger model when you hit a hard problem — architecture decisions, subtle bugs, plan critique, tricky logic.' It specifies the verb ('think', 'delegates deep reasoning') and resource ('Athena', 'stronger model'), and distinguishes it from alternatives by noting 'Athena has NO tools; she only reasons and returns a concise response.' With no sibling tools, this level of specificity is excellent.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool: 'when you hit a hard problem — architecture decisions, subtle bugs, plan critique, tricky logic.' It also clearly states when not to use it: 'Does not modify files, run commands, or access the network beyond the reasoning call.' With no sibling tools, this covers all necessary usage context, including exclusions and prerequisites like gathering context manually.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool updatev0.3.0
    • First observedthink

TDQS

A4.1/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of confusion or overlap between tools. The single tool 'think' has a clearly defined and distinct purpose focused solely on deep reasoning without any competing alternatives.

Naming Consistency5/5

A single tool inherently exhibits perfect naming consistency, as there are no other tools to compare against. The tool name 'think' is straightforward and follows a simple verb pattern without any conflicting conventions.

Tool Count2/5

A single tool is generally too few for most server purposes, as it severely limits functionality and scope. While the tool is well-defined for reasoning tasks, the server lacks breadth, making it feel thin and potentially incomplete for broader applications.

Completeness2/5

The server is severely incomplete for any domain beyond basic reasoning, as it only offers a single tool for deep thinking without supporting actions like file modification, command execution, or network access. This creates significant gaps that will likely cause agent failures in practical workflows.

Maintenance

ActivityInactive
ResponsivenessNo issues

Related MCP Connectors

Related MCP Servers

  • A
    license
    Not graded
    quality
    D
    maintenance
    An MCP server that implements the 'think' tool, providing Claude with a dedicated space for structured thinking during complex problem-solving tasks to improve reasoning capabilities.
    130
    MIT
  • A
    license
    A
    quality
    D
    maintenance
    A minimal MCP Server that provides Claude AI models with the 'think' tool capability, enabling better performance on complex reasoning tasks by allowing the model to pause during response generation for additional thinking steps.
    1
    44 npm
    25
    MIT
  • A
    license
    A
    quality
    D
    maintenance
    An MCP server implementation of Anthropic's Think Tool prompt engineering technique that enables Claude to break down complex problems and enhance its reasoning capabilities by providing a simple tool that echoes back thoughts.
    1
    2
    ISC
  • A
    license
    B
    quality
    F
    maintenance
    An MCP server that provides a "think" tool enabling structured reasoning for AI agents, allowing them to pause and record explicit thoughts during complex tasks or multi-step tool use.
    1
    23 PyPI
    107
    MIT