Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
91
71%
Does it follow best practices?
Impact
93%
2.21xAverage score across 10 eval scenarios
Low
Low-risk findings worth noting
Fix and improve this skill with Tessl
tessl review fix ./skills/anthropic-mcp-builder/SKILL.mdThe canonical home for this skill is jbvc/mcp-builder
Low
Low-risk findings.
2 low severity findings. Worth noting, but not necessarily harmful.
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Yes — SKILL.md explicitly requires fetching public web pages (e.g., "Start with the sitemap at https://modelcontextprotocol.io/sitemap.xml" and "Use WebFetch to load https://raw.githubusercontent.com/.../README.md") and instructs using web search/WebFetch as part of the required Phase 1 workflow, so the agent is expected to read untrusted third‑party content that can materially influence tool design and subsequent actions.
The skill fetches instructions or code from an external URL at runtime, and the fetched content directly controls the agent’s prompts or executes code. This dynamic dependency allows the external source to modify the agent’s behavior without any changes to the skill itself.
The evaluation harness connects at runtime to an external MCP server URL (e.g., https://example.com/mcp) to load tool definitions that are injected into the model as tools and to invoke those tools remotely (call_tool), which directly controls agent behavior and executes remote code.
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