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pleaseai/mcp-dev

Guide for creating high-quality MCP servers with best practices, TypeScript/Python patterns, and evaluation tools

63

Quality

79%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

Overview
Quality
Evals
Security
Files

Quality

Content

50%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is well-structured as a phased overview that progressively discloses detail to reference files, but every referenced file is missing, the core tool-implementation guidance lacks inline executable code, and validation feedback loops are only implicit. It is competent but unfinished in practice.

Suggestions

Provide the missing bundle files (mcp_best_practices.md, node_mcp_server.md, python_mcp_server.md, evaluation.md) under ./reference/ so the progressive-disclosure links resolve, or inline the essential content and remove the dead links.

Add at least one complete, executable tool-registration example inline (e.g., a Zod inputSchema + a server.registerTool or @mcp.tool handler with outputSchema) so the implementation phase is copy-paste-ready rather than description-only.

Make validation feedback loops explicit in Phase 3 (e.g., 'Run npm run build; if it fails, fix errors and re-run; only proceed when compilation passes' and 'Iterate in MCP Inspector until tool calls succeed') to lift workflow clarity above implicit checkpoints.

DimensionReasoningScore

Conciseness

Largely bullet/checklist based and assumes MCP familiarity, but includes unnecessary padding such as the parenthetical justifying TypeScript ('AI models are good at generating TypeScript code…'), the Overview restatement of the description, and the prose 'API Coverage vs. Workflow Tools' tradeoff — efficient but could be tightened, matching the level-2 anchor rather than the lean level-3 anchor.

2 / 3

Actionability

Provides some concrete commands (`npm run build`, `npx @modelcontextprotocol/inspector`, `python -m py_compile`, sitemap URL, a complete XML example), but the central task of implementing tools has no inline executable code — only descriptions ('Use Zod', 'Define outputSchema', 'Create shared utilities') that defer to reference files, fitting the level-2 'some concrete guidance but incomplete' anchor and falling short of copy-paste-ready level 3.

2 / 3

Workflow Clarity

Four numbered phases with sub-steps and a dedicated Review/Test phase give a clear sequence, but validation checkpoints are implicit — there is no explicit validate→fix→retry feedback loop (e.g., 'if build fails, fix and re-run; only proceed when it passes'), matching the level-2 'sequence present but checkpoints missing or implicit' anchor rather than the explicit-checkpoint level 3.

2 / 3

Progressive Disclosure

The body follows the correct one-level-deep pattern with clearly labeled references (📋/🐍/⚡/✅) to mcp_best_practices.md, node_mcp_server.md, python_mcp_server.md, and evaluation.md, but none of these files exist — the `reference/` directory is absent — so every reference is a dead link and navigation breaks, capping it at level 2 ('some structure but… not clearly organized/easy navigation') rather than the resolving-references level 3.

2 / 3

Total

8

/

12

Passed

Description

100%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is concise, specific, and uses third-person voice with an explicit 'Use when…' trigger clause. It clearly communicates both the capability and the invocation conditions with natural trigger terms and a distinct niche.

DimensionReasoningScore

Specificity

Names multiple concrete actions ('creating high-quality MCP servers', 'integrate external APIs or services') plus specific languages/frameworks (Python/FastMCP, Node/TypeScript MCP SDK), matching the 'lists multiple specific concrete actions' anchor rather than the domain-only level 2.

3 / 3

Completeness

Explicitly states both what it does ('Guide for creating high-quality MCP servers…') and when to use it ('Use when building MCP servers to integrate external APIs or services…'), satisfying the level-3 'both what AND when with explicit triggers' anchor and exceeding the level-2 cap where 'when' is only implied.

3 / 3

Trigger Term Quality

'Use when building MCP servers to integrate external APIs or services… Python (FastMCP)… Node/TypeScript (MCP SDK)' covers natural terms a user would say when requesting this skill; not merely jargon, so it clears the level-3 'good coverage' anchor over the level-2 'some keywords' anchor.

3 / 3

Distinctiveness Conflict Risk

Targets a clear, narrow niche (MCP server construction) with distinct triggers (MCP, FastMCP, MCP SDK, external API integration) unlikely to fire for unrelated skills, matching the level-3 'clear niche with distinct triggers' anchor rather than the overlapping level-2 anchor.

3 / 3

Total

12

/

12

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

relative_links

Relative link issues: 10 missing

Warning

Total

15

/

16

Passed

Reviewed

Table of Contents