General
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### Markdown Format (`response_format=markdown`
typically default)
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Explore
Find agent skills by outcome
119,390 skills indexed with the new KISS metadata standard.
Showing 24 of 119,390Categories: Coding & Debugging, Data, Communication, Cursor-rules, General
Data
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- **Return pagination metadata**: Include `has_more`
`next_offset`/`next_cursor`
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General
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- Use headers
lists
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General
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- Provide tool annotations (readOnlyHint
destructiveHint
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General
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1. **Use snake_case**: `search_users`
`create_project`
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General
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The name should be general
descriptive of the service being integrated
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General
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- Examples: `slack-mcp-server`
`github-mcp-server`
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General
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- Examples: `slack_mcp`
`github_mcp`
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General
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- **stdio**: For local integrations
command-line tools
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General
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- **Streamable HTTP**: For remote servers
multi-client scenarios
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General
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- Return `has_more`
`next_offset`
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General
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- Example: `slack_send_message`
`github_create_issue`
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General
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- **Node/TypeScript**: `{service}-mcp-server` (e.g.
`slack-mcp-server`)
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Coding & Debugging
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- **Python**: `{service}_mcp` (e.g.
`slack_mcp`)
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General
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3. **Question Generation**: Create 10 complex
realistic questions
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General
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- **Verifiable**: Single
clear answer that can be verified by string comparison
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General
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To create effective evaluations
follow the process outlined in the evaluation guide:
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General
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After implementing your MCP server
create comprehensive evaluations to test its effectiveness.
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General
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Use evaluations to test whether LLMs can effectively use your MCP server to answer realistic
complex questions.
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General
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- [⚡ TypeScript Guide](./reference/node_mcp_server.md) - Project structure
package.json
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Coding & Debugging
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Prioritize comprehensive API coverage. List endpoints to implement
starting with the most common operations.
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Coding & Debugging
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- [🐍 Python Guide](./reference/python_mcp_server.md) - Module organization
dependencies
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Coding & Debugging
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Review the service's API documentation to identify key endpoints
authentication requirements
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Coding & Debugging
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- **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
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