Mcp server builder
Skill yeaight7/agent-powerups/plugins/mcp-development/skills/mcp-server-builder
Design high-quality MCP servers around workflows, narrow schemas, context-aware outputs, and actionable errors. Use when building or reviewing MCP tools for real agent tasks.From its SKILL.md
npx -y skills add yeaight7/agent-powerups --skill mcp-server-builderAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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SKILL.md
3.5 KB, 731 tokens by cl100k_base, as published. Nobody here has run it
MCP Server Builder
Use this skill when designing or implementing an MCP server.
When to Use
- Building a new MCP server from scratch.
- Refactoring a weak or over-thin MCP tool surface.
- Reviewing whether a server exposes the right workflows.
- Designing evaluation cases for MCP usability.
Core Principles
- Build workflow tools, not thin endpoint wrappers — one tool should complete a meaningful agent task, not expose a single API method.
- Keep input schemas narrow and typed — reject unknown fields; use enums over free strings where possible.
- Return high-signal, size-bounded outputs — default to concise; add
detailorverboseflags when larger payloads are occasionally useful. - Make error messages corrective — tell the agent what to do next, not just what went wrong.
- Prefer human-meaningful identifiers over opaque IDs when both are available.
- Design evaluation cases before declaring the server "done".
Workflow
1. Map the workflow
- Identify the real tasks an agent must complete, not the underlying API surface.
- Merge low-level steps into meaningful operations (e.g., one
create_and_publishtool instead of separatecreate,validate,publish).
2. Design the tool surface
tool name: stable, verb-noun, describes the workflow step
input schema: typed, narrow, required fields only + optional detail flags
output shape: consistent structure across all tools in the server
failure modes: named error codes + correction hint
3. Design for context limits
- Default response fits in ~500 tokens for list operations, ~1500 for detail operations.
- Add
limit,page, orsummaryparameters for large result sets. - Truncate deterministically (e.g., top N by recency) — never truncate randomly.
4. Design corrective errors
Bad error: "Error: 404 Not Found"
Good error: "Resource 'project-123' not found. Use list_projects to see available project IDs."
Every error should tell the agent its next valid action.
5. Implement shared infrastructure first
- Auth handling and token refresh.
- Retry logic with exponential backoff and rate-limit awareness.
- Pagination helpers.
- Output formatting helpers (consistent truncation, redaction of secrets).
6. Evaluate before shipping
- Write representative task scenarios (not unit tests for individual tools).
- Check whether an agent can complete the full workflow using only the exposed tools.
- Redesign weak tools before adding more tools — more tools is not always better.
Server Readiness Checklist
- Every tool completes a meaningful workflow step.
- All inputs are typed and schema-validated.
- Output size is bounded by default.
- All error messages include a correction hint.
- Auth and retry are handled in shared infrastructure.
- At least one end-to-end task scenario has been tested.
- No secrets appear in tool outputs or error messages.
Local References
reference/mcp_best_practices.mdreference/python_mcp_server.mdreference/node_mcp_server.mdreference/evaluation.md
Use the Python and Node references only for the stack you are actually shipping.
Bundled Scripts
scripts/evaluation.py— evaluation scaffoldingscripts/connections.py— connection-oriented examples
Use them as optional helpers, not mandatory runtime requirements.
What ships with it: 8 files
120.2 KB alongside SKILL.md, 2 of them executable
reference/
- evaluation.md21.1 KB
- mcp_best_practices.md27.7 KB
- node_mcp_server.md26.1 KB
- python_mcp_server.md25.6 KB
scripts/
- connections.pyruns4.8 KB
- evaluation.pyruns13.7 KB
- example_evaluation.xml1.2 KB
- requirements.txt37 B
Gives 0 of the 12 instructions most mcp tooling skills give in 731 tokens
Counted across 638 of the 750 authors here whose files we hold, read 2026-08-07
- Create ten complex or independent read-only evaluation questionsin 69 of 638, across 15 files
- Test servers using MCP Inspectorin 61 of 638, across 19 files
- Provide actionable error messages with specific next stepsin 54 of 638, across 12 files
- Prioritize comprehensive API coverage over specific workflows or workflow toolsin 54 of 638, across 12 files
- Use TypeScript and Streamable HTTP for remote servers or clientsin 54 of 638, across 8 files
- Define structured output schemas where possiblein 50 of 638, across 8 files
- Use Zod or Pydantic for input schemasin 47 of 638, across 5 files
- Fetch MCP specification pages with markdown suffixin 46 of 638, across 4 files
- Load framework documentation using WebFetchin 45 of 638, across 3 files
- Verify each evaluation answer independentlyin 45 of 638, across 3 files
- Implement API client with authentication and paginationin 45 of 638, across 3 files
- Define input schemas with validationin 27 of 638, across 9 files
Said here and by no other author read
- keep input schemas narrow and typed
- return size-bounded outputs by default
- design evaluation cases before shipping
- merge low-level steps into meaningful operations
- truncate output deterministically
- handle auth and retries in shared infrastructure
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.