# Send Mcp Builder test to your agent Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually. ## Fast path - Download the package from Yavira. - Extract it into a folder your agent can access. - Paste one of the prompts below and point your agent at the extracted folder. ## Suggested prompts ### New install ```text I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete. ``` ### Upgrade existing ```text I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run. ``` ## Machine-readable fields ```json { "schemaVersion": "1.0", "item": { "slug": "unique-mcp-builder-test", "name": "Mcp Builder test", "source": "tencent", "type": "skill", "category": "开发ε·₯ε…·", "sourceUrl": "https://clawhub.ai/uniquevme/unique-mcp-builder-test", "canonicalUrl": "https://clawhub.ai/uniquevme/unique-mcp-builder-test", "targetPlatform": "OpenClaw" }, "install": { "downloadUrl": "/downloads/unique-mcp-builder-test", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=unique-mcp-builder-test", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "packageFormat": "ZIP package", "primaryDoc": "SKILL.md", "includedAssets": [ "SKILL.md", "reference/evaluation.md", "reference/mcp_best_practices.md", "reference/node_mcp_server.md", "reference/python_mcp_server.md", "scripts/connections.py" ], "downloadMode": "redirect", "sourceHealth": { "source": "tencent", "slug": "unique-mcp-builder-test", "status": "healthy", "reason": "direct_download_ok", "recommendedAction": "download", "checkedAt": "2026-05-05T10:19:55.390Z", "expiresAt": "2026-05-12T10:19:55.390Z", "httpStatus": 200, "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=unique-mcp-builder-test", "contentType": "application/zip", "probeMethod": "head", "details": { "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=unique-mcp-builder-test", "contentDisposition": "attachment; filename=\"unique-mcp-builder-test-0.1.0.zip\"", "redirectLocation": null, "bodySnippet": null, "slug": "unique-mcp-builder-test" }, "scope": "item", "summary": "Item download looks usable.", "detail": "Yavira can redirect you to the upstream package for this item.", "primaryActionLabel": "Download for OpenClaw", "primaryActionHref": "/downloads/unique-mcp-builder-test" }, "validation": { "installChecklist": [ "Use the Yavira download entry.", "Review SKILL.md after the package is downloaded.", "Confirm the extracted package contains the expected setup assets." ], "postInstallChecks": [ "Confirm the extracted package includes the expected docs or setup files.", "Validate the skill or prompts are available in your target agent workspace.", "Capture any manual follow-up steps the agent could not complete." ] } }, "links": { "detailUrl": "https://openagent3.xyz/skills/unique-mcp-builder-test", "downloadUrl": "https://openagent3.xyz/downloads/unique-mcp-builder-test", "agentUrl": "https://openagent3.xyz/skills/unique-mcp-builder-test/agent", "manifestUrl": "https://openagent3.xyz/skills/unique-mcp-builder-test/agent.json", "briefUrl": "https://openagent3.xyz/skills/unique-mcp-builder-test/agent.md" } } ``` ## Documentation ### Overview Create MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. The quality of an MCP server is measured by how well it enables LLMs to accomplish real-world tasks. ### πŸš€ High-Level Workflow Creating a high-quality MCP server involves four main phases: ### Phase 1: Deep Research and Planning 1.1 Understand Modern MCP Design API Coverage vs. Workflow Tools: Balance comprehensive API endpoint coverage with specialized workflow tools. Workflow tools can be more convenient for specific tasks, while comprehensive coverage gives agents flexibility to compose operations. Performance varies by clientβ€”some clients benefit from code execution that combines basic tools, while others work better with higher-level workflows. When uncertain, prioritize comprehensive API coverage. Tool Naming and Discoverability: Clear, descriptive tool names help agents find the right tools quickly. Use consistent prefixes (e.g., github_create_issue, github_list_repos) and action-oriented naming. Context Management: Agents benefit from concise tool descriptions and the ability to filter/paginate results. Design tools that return focused, relevant data. Some clients support code execution which can help agents filter and process data efficiently. Actionable Error Messages: Error messages should guide agents toward solutions with specific suggestions and next steps. 1.2 Study MCP Protocol Documentation Navigate the MCP specification: Start with the sitemap to find relevant pages: https://modelcontextprotocol.io/sitemap.xml Then fetch specific pages with .md suffix for markdown format (e.g., https://modelcontextprotocol.io/specification/draft.md). Key pages to review: Specification overview and architecture Transport mechanisms (streamable HTTP, stdio) Tool, resource, and prompt definitions 1.3 Study Framework Documentation Recommended stack: Language: TypeScript (high-quality SDK support and good compatibility in many execution environments e.g. MCPB. Plus AI models are good at generating TypeScript code, benefiting from its broad usage, static typing and good linting tools) Transport: Streamable HTTP for remote servers, using stateless JSON (simpler to scale and maintain, as opposed to stateful sessions and streaming responses). stdio for local servers. Load framework documentation: MCP Best Practices: πŸ“‹ View Best Practices - Core guidelines For TypeScript (recommended): TypeScript SDK: Use WebFetch to load https://raw.githubusercontent.com/modelcontextprotocol/typescript-sdk/main/README.md ⚑ TypeScript Guide - TypeScript patterns and examples For Python: Python SDK: Use WebFetch to load https://raw.githubusercontent.com/modelcontextprotocol/python-sdk/main/README.md 🐍 Python Guide - Python patterns and examples 1.4 Plan Your Implementation Understand the API: Review the service's API documentation to identify key endpoints, authentication requirements, and data models. Use web search and WebFetch as needed. Tool Selection: Prioritize comprehensive API coverage. List endpoints to implement, starting with the most common operations. ### Phase 2: Implementation 2.1 Set Up Project Structure See language-specific guides for project setup: ⚑ TypeScript Guide - Project structure, package.json, tsconfig.json 🐍 Python Guide - Module organization, dependencies 2.2 Implement Core Infrastructure Create shared utilities: API client with authentication Error handling helpers Response formatting (JSON/Markdown) Pagination support 2.3 Implement Tools For each tool: Input Schema: Use Zod (TypeScript) or Pydantic (Python) Include constraints and clear descriptions Add examples in field descriptions Output Schema: Define outputSchema where possible for structured data Use structuredContent in tool responses (TypeScript SDK feature) Helps clients understand and process tool outputs Tool Description: Concise summary of functionality Parameter descriptions Return type schema Implementation: Async/await for I/O operations Proper error handling with actionable messages Support pagination where applicable Return both text content and structured data when using modern SDKs Annotations: readOnlyHint: true/false destructiveHint: true/false idempotentHint: true/false openWorldHint: true/false ### Phase 3: Review and Test 3.1 Code Quality Review for: No duplicated code (DRY principle) Consistent error handling Full type coverage Clear tool descriptions 3.2 Build and Test TypeScript: Run npm run build to verify compilation Test with MCP Inspector: npx @modelcontextprotocol/inspector Python: Verify syntax: python -m py_compile your_server.py Test with MCP Inspector See language-specific guides for detailed testing approaches and quality checklists. ### Phase 4: Create Evaluations After implementing your MCP server, create comprehensive evaluations to test its effectiveness. Load βœ… Evaluation Guide for complete evaluation guidelines. 4.1 Understand Evaluation Purpose Use evaluations to test whether LLMs can effectively use your MCP server to answer realistic, complex questions. 4.2 Create 10 Evaluation Questions To create effective evaluations, follow the process outlined in the evaluation guide: Tool Inspection: List available tools and understand their capabilities Content Exploration: Use READ-ONLY operations to explore available data Question Generation: Create 10 complex, realistic questions Answer Verification: Solve each question yourself to verify answers 4.3 Evaluation Requirements Ensure each question is: Independent: Not dependent on other questions Read-only: Only non-destructive operations required Complex: Requiring multiple tool calls and deep exploration Realistic: Based on real use cases humans would care about Verifiable: Single, clear answer that can be verified by string comparison Stable: Answer won't change over time 4.4 Output Format Create an XML file with this structure: Find discussions about AI model launches with animal codenames. One model needed a specific safety designation that uses the format ASL-X. What number X was being determined for the model named after a spotted wild cat? 3 ### πŸ“š Documentation Library Load these resources as needed during development: ### Core MCP Documentation (Load First) MCP Protocol: Start with sitemap at https://modelcontextprotocol.io/sitemap.xml, then fetch specific pages with .md suffix πŸ“‹ MCP Best Practices - Universal MCP guidelines including: Server and tool naming conventions Response format guidelines (JSON vs Markdown) Pagination best practices Transport selection (streamable HTTP vs stdio) Security and error handling standards ### SDK Documentation (Load During Phase 1/2) Python SDK: Fetch from https://raw.githubusercontent.com/modelcontextprotocol/python-sdk/main/README.md TypeScript SDK: Fetch from https://raw.githubusercontent.com/modelcontextprotocol/typescript-sdk/main/README.md ### Language-Specific Implementation Guides (Load During Phase 2) 🐍 Python Implementation Guide - Complete Python/FastMCP guide with: Server initialization patterns Pydantic model examples Tool registration with @mcp.tool Complete working examples Quality checklist ⚑ TypeScript Implementation Guide - Complete TypeScript guide with: Project structure Zod schema patterns Tool registration with server.registerTool Complete working examples Quality checklist ### Evaluation Guide (Load During Phase 4) βœ… Evaluation Guide - Complete evaluation creation guide with: Question creation guidelines Answer verification strategies XML format specifications Example questions and answers Running an evaluation with the provided scripts ## Trust - Source: tencent - Verification: Indexed source record - Publisher: uniquevme - Version: 0.1.0 ## Source health - Status: healthy - Item download looks usable. - Yavira can redirect you to the upstream package for this item. - Health scope: item - Reason: direct_download_ok - Checked at: 2026-05-05T10:19:55.390Z - Expires at: 2026-05-12T10:19:55.390Z - Recommended action: Download for OpenClaw ## Links - [Detail page](https://openagent3.xyz/skills/unique-mcp-builder-test) - [Send to Agent page](https://openagent3.xyz/skills/unique-mcp-builder-test/agent) - [JSON manifest](https://openagent3.xyz/skills/unique-mcp-builder-test/agent.json) - [Markdown brief](https://openagent3.xyz/skills/unique-mcp-builder-test/agent.md) - [Download page](https://openagent3.xyz/downloads/unique-mcp-builder-test)