Sensei MCP
MCP先生
Sensei MCPは、Starknet上でDojoとCairoの開発に関する専門家のガイダンスを提供するModel Context Protocol(MCP)サーバーです。あなた専用のDojo Senseiとして機能し、Dojo Entity Component System(ECS)フレームワークを用いたオンチェーンワールド構築に関する専門知識とサポートを提供します。
特徴
専門家によるCairoガイダンス:Cairo独自の所有権、メモリ、型システムに関するヘルプを入手
Dojo ECS アーキテクチャ: モデル、システム、ワールドパターンについて学ぶ
スマートコントラクト開発:Starknetスマートコントラクトのベストプラクティス
専用ツール: モデル、システム、テストなどのトピック固有のツールにアクセスします
Related MCP server: Starknet MCP Server
インストール
カーソルの使用
Sensei をカーソル IDE に追加するには:
カーソル設定を開く (⌘+,)
「MCP」セクションに移動します
「新しいMCPを追加」をクリックします
次のように設定します。
名前:先生(または好きな名前)
タイプ: コマンド
コマンド:
npx github:dojoengine/sensei-mcp
「保存」をクリック
設定が完了すると、次の方法で Sensei にアクセスできます。
コマンドパレットを開く (⌘+K)
「MCP」と入力し、「MCPチャットを開く」を選択します
MCPドロップダウンから「Sensei」を選択する
Sensei は、Starknet 開発のベスト プラクティスに関する深い知識を活かして、Dojo および Cairo 開発に関する質問に専門的なサポートを提供します。
カーソルエージェントの使用
Sensei を Cursor Agent と併用する場合は、最適な結果を得るために次のベスト プラクティスに従ってください。
常に特殊なツールについて言及する: エージェントに Sensei の特殊なツールを使用するように明示的に依頼します (例: 「モデルの作成に dojo_model ツールを使用してください」)。
増分開発アプローチに従います。
dojo_101を使用してプロジェクトのセットアップを開始するまず
dojo_modelを使ってモデルを定義する次に
dojo_logicを使ってシステムを実装する最後に
dojo_configを使用してプロジェクトを構成します。dojo_testを使用してテストを追加する
リクエストは具体的にしてください。たとえば、「Dojo ゲームを手伝ってください」と尋ねる代わりに、「dojo_model ツールを使用して、ゲームの位置モデルを作成してください」と言います。
複雑なタスクを分割する: ゲーム全体の実装を一度に依頼するのではなく、一度に 1 つのコンポーネントについて支援を求めます。
プロンプトの例:
I'm building a Dojo game. First, please use the dojo_101 tool to help me set up the project structure.
After that, I'll need help creating the models using the dojo_model tool.直接実行
Sensei MCP を直接実行することもできます。
npx github:dojoengine/sensei-mcp利用可能なツール
Sensei は、Dojo 開発のさまざまな側面に特化したツールを提供します。
dojo_101 : 初心者向けのDojo開発入門
dojo_config : Dojo プロジェクトを構成するための必須のガイダンス
dojo_logic : Dojo システムとゲーム ロジックの実装に関する専門家のガイダンス
dojo_model : Dojo モデルの作成と操作に関する専門的なガイダンス
dojo_test : Dojo アプリケーションのテストを書くための包括的なガイド
dojo_token : Dojo でトークン標準を実装するための詳細なガイド
ツールの使い方
Sensei とチャットするときに、ツール名を言及することで具体的なガイダンスを求めることができます。
Can you help me understand how to create a model in Dojo?Sensei は適切なツール (この場合はdojo_model ) を自動的に使用して、専門的なガイダンスを提供します。
推奨開発ワークフロー
最良の結果を得るには、次の増分開発アプローチに従ってください。
プロジェクトのセットアップ(
dojo_101を使用)sozo initでプロジェクトを初期化するプロジェクト構造を理解する
定型コードを削除または置き換える
モデルを定義する(
dojo_modelを使用)ゲーム状態モデルを作成する
適切な特性の導出を確実にする
キーフィールドを正しく設定する
システムを実装する(
dojo_logicを使用)システム契約を作成する
ゲームの仕組みを実装する
状態の変化を処理する
プロジェクト構成(
dojo_configを使用)Scarb.toml を設定する
Dojoプロファイルを構成する
依存関係を管理する
テスト(
dojo_testを使用)包括的なテストを書く
ゲームロジックを検証する
このワークフローにより、開発の適切な段階で各ツールの専門知識を活用し、構造化された体系的な方法で Dojo アプリケーションを構築できます。
コア専門知識
Sensei は以下の分野において深い専門知識を持っています:
Cairo プログラミング言語 (独自の所有権、メモリ、型システムを含む)
Dojo ECS アーキテクチャ (モデル、システム、ワールド)
Starknetでのスマートコントラクト開発
オンチェーンゲーム開発のベストプラクティス
発達
プロジェクト構造
bin/: 実行可能スクリプトが含まれていますsrc/: MCPサーバーのソースコードprompts/: Dojo 開発のさまざまな側面に関するテキストプロンプトresources/: プロンプトで使用される追加リソース
ソースから構築
# Clone the repository
git clone https://github.com/dojoengine/sensei-mcp.git
cd sensei-mcp
# Install dependencies
npm install
# Build the project
npm run build
# Start the server
npm startAvailable Tools
7 toolsdojo_101A
Beginner-friendly introduction to Dojo development. Use this when starting a new Dojo project, understanding the basic workflow, or when you need a high-level overview of the Dojo development process and architecture.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It describes the tool as an 'introduction' and 'overview', which suggests it's informational and non-destructive. However, it doesn't specify behavioral traits like whether it's interactive, returns structured data, or has any side effects. The description adds context about its beginner-friendly nature but lacks details on execution behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose ('Beginner-friendly introduction to Dojo development') and follows with specific usage scenarios in a single, efficient sentence. Every part adds value without redundancy, making it appropriately sized and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (introductory, 0 parameters) and lack of annotations/output schema, the description is reasonably complete. It explains the purpose, usage, and scope. However, it could be more complete by hinting at what the output might contain (e.g., tutorial steps, explanations) since there's no output schema, but it's adequate for this simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, but it appropriately doesn't mention any. Baseline for 0 parameters is 4, as it avoids unnecessary parameter discussion.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Beginner-friendly introduction to Dojo development' with specific verbs like 'starting a new Dojo project', 'understanding the basic workflow', and 'high-level overview of the Dojo development process and architecture'. It distinguishes itself from siblings like dojo_config, dojo_logic, etc., which likely handle specific technical aspects rather than introductory guidance.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool: 'Use this when starting a new Dojo project, understanding the basic workflow, or when you need a high-level overview'. It implies alternatives by distinguishing itself from sibling tools that likely serve more advanced or specific purposes, though it doesn't explicitly name them.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
dojo_configB
Essential guidance for configuring Dojo projects. Use this when setting up Scarb.toml, creating dojo profile files, configuring permissions, setting up namespaces, or managing external contracts and dependencies.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. The description mentions 'guidance' and configuration activities but doesn't clarify whether this tool performs actions, provides information, modifies files, or requires specific permissions. It fails to disclose key behavioral traits like whether it's read-only, destructive, or has side effects, which is a significant gap for a configuration tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: the first states the purpose, and the second provides usage guidelines. It's reasonably concise but could be more front-loaded with a clearer action verb. The phrase 'Essential guidance' is somewhat vague, and the list of configuration activities feels like it's trying to cover too much ground without clarifying the tool's core function. It's adequately structured but not optimally efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of configuration tools and the lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool actually does (e.g., returns configuration templates, validates settings, applies changes) or what users can expect as a result. For a tool with no structured data to rely on, the description should provide more complete context about behavior and outcomes.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the absence of parameters. The description doesn't need to add parameter information, and it appropriately doesn't mention any parameters. This meets the baseline of 4 for tools with no parameters, as there's no gap to compensate for.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool provides 'essential guidance for configuring Dojo projects' which gives a general purpose, but it's vague about what specific action the tool performs. It lists several configuration activities (setting up Scarb.toml, creating profile files, etc.) but doesn't specify whether this tool performs these actions, helps with them, or provides information about them. The purpose is clear enough to understand the domain but lacks specificity about the tool's actual function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states 'Use this when' followed by a list of configuration scenarios, providing clear context for when to invoke this tool. However, it doesn't mention when NOT to use it or how it differs from sibling tools like dojo_101, dojo_logic, or dojo_model, which might also relate to Dojo project configuration. The guidance is helpful but lacks sibling differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
dojo_logicA
Expert guidance on implementing Dojo systems and game logic. Use this when writing contract functions, implementing game mechanics, handling state changes, or working with the World contract to read/write models.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions 'expert guidance' but doesn't disclose behavioral traits like whether it's read-only, requires authentication, has rate limits, or what form the guidance takes (e.g., code examples, explanations). This leaves significant gaps for a tool that likely provides advisory output.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences that are front-loaded with the purpose and followed by specific usage contexts. Every phrase adds value without redundancy, making it efficiently structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of providing 'expert guidance' on Dojo systems, the description lacks details on output format, depth of guidance, or examples. With no annotations and no output schema, it's incomplete for understanding what the tool actually returns, though it adequately covers when to use it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, earning a baseline score of 4 for not adding unnecessary information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides 'expert guidance on implementing Dojo systems and game logic,' which is a specific purpose. It distinguishes from siblings by focusing on implementation guidance rather than configuration, modeling, or other aspects. However, it doesn't explicitly contrast with each sibling tool's function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance with 'Use this when writing contract functions, implementing game mechanics, handling state changes, or working with the World contract to read/write models.' This gives clear contexts for when to invoke the tool, though it doesn't specify when NOT to use it or name alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
dojo_modelA
Specialized guidance for creating and working with Dojo models. Use this when you need to define data structures, create model schemas, implement model traits, or understand model relationships and constraints.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
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. While it mentions the tool provides 'guidance,' it doesn't clarify whether this is informational (read-only), interactive, or involves any side effects like creating/modifying files. For a tool with zero annotation coverage, this leaves significant gaps in understanding its operational behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured in two sentences: the first states the core purpose, and the second provides specific usage examples. Every word contributes to understanding the tool's function, with no wasted text or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters (schema coverage 100%) and no output schema, the description adequately covers the 'what' and 'when' aspects. However, as a tool with no annotations, it lacks details about behavioral traits (e.g., whether it's read-only, has side effects, or requires specific permissions), making it incomplete for full agent understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately focuses on the tool's purpose and usage without attempting to describe nonexistent parameters, earning a high baseline score for not adding unnecessary information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as providing 'specialized guidance for creating and working with Dojo models' and lists specific activities like defining data structures, creating model schemas, implementing model traits, and understanding relationships/constraints. This gives a comprehensive view of what the tool does, though it doesn't explicitly differentiate from sibling tools like dojo_config or dojo_logic.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool ('Use this when you need to define data structures, create model schemas, implement model traits, or understand model relationships and constraints'), which gives practical guidance. However, it doesn't mention when NOT to use it or explicitly name alternatives among the sibling tools, preventing a perfect score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
dojo_senseiB
The main system prompt for Dojo development. Use this as the primary prompt when starting a conversation about Dojo or Cairo development, or when you need comprehensive guidance across all aspects of Dojo development.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions providing 'comprehensive guidance' but doesn't describe how it behaves—e.g., whether it generates interactive prompts, returns static text, handles follow-ups, or has any limitations like response length or rate. This leaves significant gaps in understanding its operational traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, stating the main purpose in the first sentence and adding usage context in the second. Both sentences earn their place by clarifying the tool's role and when to use it, with no wasted words. However, it could be slightly more structured by explicitly listing key aspects of 'comprehensive guidance'.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters, no annotations, and no output schema, the description provides basic purpose and usage guidelines, which is adequate for a simple prompt tool. However, it lacks details on behavioral aspects (e.g., output format, interaction model) and doesn't differentiate from siblings, making it incomplete for optimal agent use in a context with multiple similar tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it appropriately doesn't mention any. A baseline of 4 is applied since no parameters exist, and the description doesn't incorrectly reference any.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool is 'the main system prompt for Dojo development' and provides 'comprehensive guidance across all aspects of Dojo development', which gives a general purpose. However, it's somewhat vague about what specific actions it performs (e.g., generating code, answering questions, providing tutorials) and doesn't clearly distinguish it from sibling tools like 'dojo_101' or 'dojo_logic' that might also offer guidance.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool: 'when starting a conversation about Dojo or Cairo development, or when you need comprehensive guidance across all aspects of Dojo development'. This provides clear context for usage, but it doesn't specify when NOT to use it or mention alternatives among the sibling tools, such as using 'dojo_101' for basics or 'dojo_config' for configuration-specific help.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
dojo_testA
Comprehensive guide for writing tests for Dojo applications. Use this when creating unit tests, integration tests, setting up test environments, or verifying the correctness of your Dojo systems and models.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It describes the tool as a 'guide,' implying it's informational and likely read-only, but does not disclose behavioral traits such as whether it modifies data, requires authentication, has rate limits, or what the output format is. This leaves significant gaps for a tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose and followed by usage guidelines. Every sentence adds value without redundancy, making it efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (likely informational with no parameters) and lack of annotations/output schema, the description is moderately complete. It explains purpose and usage but lacks details on behavior and output, which are important for a guide tool. It's adequate but has clear gaps in transparency.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description does not mention parameters, which is appropriate. Baseline is 4 for 0 parameters, as it avoids unnecessary information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as a 'Comprehensive guide for writing tests for Dojo applications,' specifying the verb 'guide' and resource 'tests for Dojo applications.' It distinguishes from siblings by focusing on testing rather than configuration, logic, models, etc., though it doesn't explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: 'when creating unit tests, integration tests, setting up test environments, or verifying the correctness of your Dojo systems and models.' This gives explicit scenarios but does not mention when not to use it or name specific alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
dojo_tokenA
Detailed guidance on implementing token standards in Dojo. Use this when creating ERC20, ERC721, or ERC1155 tokens, implementing token functionality, or integrating tokens with your Dojo game.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. The description only states it provides 'guidance' but doesn't clarify what that means operationally - is it documentation retrieval, code generation, validation, or something else? It doesn't mention whether this tool performs any actions (like generating files), requires specific permissions, has side effects, or what format the guidance comes in. For a tool with zero annotation coverage, this is insufficient behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly concise with two sentences that each earn their place. The first sentence establishes the core purpose ('Detailed guidance on implementing token standards in Dojo'), and the second sentence provides specific usage contexts. There's zero waste or redundancy, and the information is front-loaded with the most important details first.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters (empty schema), no annotations, and no output schema, the description provides adequate basic context about what the tool is for. However, it doesn't explain what form the 'guidance' takes or what the user can expect as a result. For a tool that presumably provides some kind of output (even if just informational), more detail about the nature of that output would improve completeness. The description is minimally viable but has clear gaps in explaining the tool's behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage (empty schema). The description doesn't need to explain any parameters since there are none. A baseline of 4 is appropriate for a zero-parameter tool where the schema fully documents the lack of parameters. The description focuses appropriately on what the tool does rather than parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides 'Detailed guidance on implementing token standards in Dojo' and lists specific use cases (ERC20, ERC721, ERC1155 tokens, implementing token functionality, integrating tokens with games). It distinguishes itself from siblings by focusing specifically on token implementation rather than general Dojo topics like configuration, logic, or testing. However, it doesn't specify the exact form of guidance (documentation, code generation, validation, etc.), keeping it at a 4 rather than a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states 'Use this when creating ERC20, ERC721, or ERC1155 tokens, implementing token functionality, or integrating tokens with your Dojo game.' This provides clear context about when to use this tool. However, it doesn't mention when NOT to use it or explicitly name alternatives among the sibling tools (like dojo_config or dojo_logic), which would be needed for a perfect score of 5.
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.
7 tool updates
v1.0.0- First observed
dojo_101 - First observed
dojo_config - First observed
dojo_logic - First observed
dojo_model - First observed
dojo_sensei - First observed
dojo_test - First observed
dojo_token
TDQS
Scored across 7 tools
Every tool has a clearly distinct purpose with no ambiguity, as each targets a specific aspect of Dojo development (e.g., introduction, configuration, logic, models, testing, tokens, and a main prompt). The descriptions clearly differentiate their scopes, such as dojo_101 for beginners versus dojo_logic for expert guidance, ensuring agents can easily select the right tool.
All tool names follow a consistent 'dojo_' prefix pattern with descriptive suffixes (e.g., dojo_config, dojo_logic, dojo_model), using snake_case uniformly. This predictable naming scheme makes it easy for agents to understand the domain and purpose at a glance, with no deviations in style or convention.
With 7 tools, the count is well-scoped for the server's purpose of Dojo development guidance, covering key areas like setup, logic, models, testing, and tokens without being overwhelming. Each tool earns its place by addressing a distinct need, making the set comprehensive yet manageable for agents.
The tool surface is nearly complete for Dojo development, covering essential aspects from beginner introduction to advanced logic, models, testing, and token standards. A minor gap exists in deployment or integration tools, but core workflows are well-covered, allowing agents to work around any missing operations effectively.
Maintenance
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The OpenZeppelin Cairo Contracts MCP server generates secure smart contracts in the Cairo language for Starknet environments based on OpenZeppelin templates. It brings OpenZeppelin's proven security and style rules directly into AI-driven development workflows to create safe, production-ready contracts. Key capabilities include providing templates for ERC-20, ERC-721, ERC-1155, Multisig, Governor, and Vesting contracts.
A Model Context Protocol server for Wix AI tools
The OpenZeppelin Solidity Contracts MCP server integrates OpenZeppelin's security and style rules into AI-driven development workflows, enabling AI assistants to generate safe, correct, and production-ready smart contracts. It automatically validates generated code against OpenZeppelin standards (including imports, modifiers, naming conventions, and security checks) and supports various contract types including ERC-20, ERC-721, ERC-1155, Stablecoins, RWA, Governor, and Account contracts through prompt-driven workflows.
A comprehensive Model Context Protocol (MCP) server that enables AI assistants to interact with yo…
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CodeAlive MCPofficial
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