This skill bootstraps a Python MCP server project with proper structure, tooling, and transport setup for rapid AI-driven workflows.
Find, trial, compare, and govern AI agents before hiring
Content
Create, refresh, evaluate, and publish docs, briefs, and reusable knowledge assets.
What team job or business role does the user need filled?
Start from a plain-language department or occupational family, then open related technical categories or job-matcher prompts.
- department or team-role discovery
- plain-language job briefs
- business outcome shortlists
- non-technical browsing
Start from user language
- Refresh docs or README guidance with verifiable source links.
- Create a reusable knowledge asset from existing project material.
Sandbox-first next steps
Content candidates
Showing 12 of 5000. Adjust filters to narrow the review list without losing job context.
This skill generates production-ready MCP servers in Python or TypeScript with Tools, Resources, and Prompts following best practices.
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Builds Model Context Protocol (MCP) servers for Claude with tools, resources, and prompts. Use when users request "create MCP server", "build Claude tool", "MCP integration", or "custom Claude tools".
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This skill helps you design, configure, and deploy MCP servers that integrate external APIs and data sources with Claude.
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This skill enables building MCP servers in Next.js with shared Zod schemas and reusable actions for consistent, scalable tooling.
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This skill helps you design, implement, and debug MCP server tools with a clear service and tool layer, type-safe results, and standardized errors.
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This skill interacts with a self-hosted Mealie instance via REST API to add, update, fetch recipes, meal plans, and shopping lists.
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This skill reviews Medusa code for guideline compliance, suggests improvements, and explains why patterns are preferred to help you write robust Medusa apps.
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This skill helps you generate memes using deep reasoning, trend analysis, and audience targeting to land laughs and drive engagement.
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This skill helps you integrate Memic into AI agents to fetch grounded context from documents and databases via a single API.
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This skill stores and retrieves cross-session user information to personalize interactions, ensuring preferences, identities, and decisions persist across
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This skill enables semantic memory for AI agents, delivering 95% token savings and rapid, context-aware recall across multi-tenant environments.
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Review links
Role-family pages stay focused on plain-language job review; complete review records and finalist profile resources stay linked here.
Supporting review linksLinks, review order, and page-specific notes remain available here.
5000 candidates for Content. Open matching profiles for fit, setup guidance, trust evidence, and sandbox trial planning.
- 01Site contextShared review rules
- 02Role familyOpen the focused review record
- 03Profile pageOpen the candidate page
- 04Profile resourcesEvidence, setup, trust, trial, and history files
Use the links and review path below for role-family candidates, job brief context, and finalist profile resources before action.