An MCP server that validates content against MCP specification using semantic search and AI
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
An MCP Server for validating code or content against the official Model Context Protocol (MCP) specification to ensure technical accuracy and prevent the spread of misinformation.
π¦ View in MCP Registry - Available in the official MCP Registry
π View Project Roadmap - See planned features and development progress
ποΈ Design Documentation - Technical design and implementation details
The MCP Fact-Check MCP Server helps ensure technical accuracy when coding or writing about MCP by comparing content against official specifications. It uses:
check_mcp_claim - Comprehensive validation of MCP-related content
check_mcp_quick_fact - Quick fact-checking for single MCP claims
search_spec - Searches MCP specifications using semantic similarity
list_spec_versions - Lists available MCP specification versions
migrate-mcp-content - Guides content migration between MCP specification versions
Parameters:
current_version (required): Source MCP specification version (e.g., "2024-11-05", "2025-06-18")target_version (required): Target MCP specification version to migrate to (e.g., "draft")update_scope (optional): Determines how aggressive the migration should be
critical_only: Fix only critical inaccuracies and breaking changes (minimal changes)enhancement_focused: Fix issues and improve clarity, align with best practicescomprehensive: Complete review with all improvements and enhanced claritycomprehensiveThe MCP Fact-Check server is available through the Model Context Protocol registry. Install it directly from your MCP client:
For Claude Desktop and other MCP clients:
That's it! The server will be automatically configured and ready to use.
For developers: If you need to build from source or contribute to the project, see INSTALL.md for development setup instructions.
For a beautiful, AI-focused trace visualization UI, set up Arize Phoenix:
What you'll see in Phoenix:
Phoenix is specifically designed for AI/ML observability and provides a much more user-friendly experience than traditional tracing tools.
The project includes pre-extracted MCP specifications and embeddings for all versions. To check when the draft specification was last updated, see data/SPEC_METADATA.json:
To update the draft specification:
To add a new specification version:
All specification extraction dates and source commits are automatically tracked in data/SPEC_METADATA.json.
Test the server using the included test client:
See DESIGN.md for the complete architecture documentation.
OPENAI_API_KEY - Required for embedding generation and content validationGITHUB_TOKEN - Optional, for higher GitHub API rate limits when extracting specsMIT License. See LICENSE for details.
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