mcp-spec-assessments

This MCP server package provides infrastructure for assessing the quality and clarity of the Model Context Protocol (MCP) specification. The repository documents an approach to using large language models (LLMs) to evaluate the specification itself, focusing on definition clarity, completeness, and correctness as a technical document. To use the tooling, start by reviewing the included assessment materials and project instructions. The workspaces and documents reference the MCP specification from the official site, the schema.ts and schema.json files, and a consolidated textual capture of the specification pages. The tools described in the repository are oriented toward automated or semi-automated review workflows: loading the specification artifacts into a reasoning environment, and applying evaluation prompts to LLMs to generate quality assessments. If you intend to run any server-like component, you would interact with the MCP assessment workflow as a consumer of the evaluation outputs rather than a live RPC server, since the repository focuses on analysis and documentation of the MCP spec rather than providing a production runtime MCP service.

Prerequisites:

• Git
• Node.js (if you plan to run any Node-based tooling) or Python (if there are Python scripts, depending on project setup)
• Basic terminal/command-line familiarity

Steps:

1. Clone the repository git clone https://github.com/<owner>/mcp-spec-assessments.git cd mcp-spec-assessments

2. Inspect project structure

   • Look for package.json or requirements.txt to determine runtime environment
   • Review /assessments and /documents for the scope of tools and data

3. Install dependencies (choose the appropriate command based on the found setup)

   • If a Node.js setup is present (package.json): npm install
   • If a Python setup is present (requirements.txt or Pipfile): python3 -m pip install -r requirements.txt

4. Run the assessment workflow (example placeholders—adjust to actual scripts in the repo):

   • Node.js example (if scripts exist): npm run start
   • Python example (if a main module exists): python3 -m mcp_spec_assessments

5. View results

   • Results are typically written to /assessments or /documents/mcp-spec-docs.txt as described in the README
   • Open the generated reports to review how the LLM assessments scored the MCP specification

Notes:

• If the repository does not include a runnable server, you will primarily interact with documents and assessment outputs rather than a live server process.

Tips and common issues:

• The quality of assessments relies on the alignment between the MCP spec source files (schema.ts, schema.json) and the website-derived content compiled in mcp-spec-docs.txt. Ensure these sources are present and up-to-date when re-running assessments.
• If you encounter missing dependencies, verify whether there is a dedicated Python virtual environment or a Node.js workspace configuration (e.g., npx or npm ci) mentioned in project docs.
• Since this repo centers on evaluating a specification, consider validating that the inputs (schema files and website text capture) reflect the latest 2025-03-26 MCP specification to avoid stale analysis.
• Environment variables, if any, would typically control paths to documents, model access tokens, or evaluation prompts. If you customize prompts, document them clearly in a local config or README to preserve reproducibility.