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mcp-factcheck

mcp-factcheck

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github.com/carlisiaDeveloper Tools3Updated 48w ago

About mcp-factcheck

mcp-factcheck is an MCP server for developers and technical writers checking MCP-related code or content. Semantic search compares claims with official specification versions, including compound claims.

Key features

  1. 01Validate content against MCP specs
  2. 02Search spec sections semantically
  3. 03Decompose and check compound claims
  4. 04Return corrections and confidence scores
  5. 05Support multiple spec versions

Use cases

  1. 01Review MCP claims in tutorials
  2. 02Check code against the specification
  3. 03Verify a single MCP fact

MCP support

The server exposes tools for content validation, quick fact-checking, specification search, and version listing to MCP clients. It also provides a prompt for migrating content between specification versions.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"carlisia-mcp-factcheck": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"OPENAI_API_KEY",
"ghcr.io/carlisia/mcp-factcheck:v1.0.0"
],
"env": {
"OPENAI_API_KEY": "<OPENAI_API_KEY>"
}
}
}
}
Run commanddocker run -i --rm -e OPENAI_API_KEY ghcr.io/carlisia/mcp-factcheck:v1.0.0
Environment variables to set
OPENAI_API_KEYSecretOpenAI API key for embedding generation and content validation

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
ocighcr.io/carlisia/mcp-factcheck:v1.0.0

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

MCP Fact-Check MCP Server

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.

📦 View in MCP Registry - Available in the official MCP Registry

📋 View Project Roadmap - See planned features and development progress

🏗️ Design Documentation - Technical design and implementation details

Overview

The MCP Fact-Check MCP Server helps ensure technical accuracy when coding or writing about MCP by comparing content against official specifications. It uses:

  • Semantic search with OpenAI embeddings to find relevant specification sections
  • AI-powered validation to detect inaccuracies and suggest corrections
  • Compound claim decomposition to validate complex statements with multiple assertions
  • Multiple spec versions support (draft, 2025-06-18, 2025-03-26, 2024-11-05)

Features

MCP Tools Exposed
  1. check_mcp_claim - Comprehensive validation of MCP-related content

    • Validates multi-claim content (documentation, tutorials, bullet points)
    • Automatically decomposes compound claims (e.g., "X and Y") for accurate validation
    • Provides step-by-step validation workflow
    • Identifies missing best practices and modal verb issues
    • Returns corrected content with confidence scores
  2. check_mcp_quick_fact - Quick fact-checking for single MCP claims

    • Validates single sentences or quick questions
    • Returns concise ✓/✗ verdict with explanation
    • Uses aggressive search strategies for accuracy
    • Perfect for "Does MCP support X?" questions
  3. search_spec - Searches MCP specifications using semantic similarity

    • Returns most relevant specification sections
    • Supports all specification versions
  4. list_spec_versions - Lists available MCP specification versions

    • Shows version dates and descriptions
    • Indicates which version is current
MCP Prompts Available
  1. migrate-mcp-content - Guides content migration between MCP specification versions

    • Validates content against source specification first
    • Identifies changes between specification versions
    • Provides step-by-step migration guidance
    • Works with any type of MCP-related content
    • Preserves the original tone, style, and voice when making corrections or suggestions

    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 practices
      • comprehensive: Complete review with all improvements and enhanced clarity
      • Default: comprehensive

Installation

The 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:

  • Search for "mcp-factcheck" in your client's server marketplace
  • Click install
  • Provide your OpenAI API key when prompted

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.

Observability
Visual Tracing with Arize Phoenix

For a beautiful, AI-focused trace visualization UI, set up Arize Phoenix:

  1. Install and start Phoenix:
# Install Phoenix
pipx install arize-phoenix

# Start Phoenix server
phoenix serve
  1. Update the Host config to send traces to Phoenix:
{
  "mcpServers": {
    "mcp-factcheck": {
      "command": "/path/to/bin/mcp-factcheck-server",
      "args": [
        "--data-dir",
        "/path/to/data/embeddings",
        "--telemetry",
        "--otlp-endpoint",
        "http://localhost:6006"
      ],
      "env": {
        "OPENAI_API_KEY": "your-api-key"
      }
    }
  }
}
  1. View traces at: http://localhost:6006

What you'll see in Phoenix:

  • Beautiful AI-focused interface designed for LLM applications
  • Complete validation pipeline timeline with clear visual hierarchy
  • Embedding generation performance and OpenAI API call tracking
  • Vector search visualization with similarity scores
  • Per-chunk validation confidence levels and quality metrics
  • Cost tracking for OpenAI API usage (or whichever llm is being used for embedding the input content/code)
  • Clean, intuitive navigation focused on AI workflows

Phoenix is specifically designed for AI/ML observability and provides a much more user-friendly experience than traditional tracing tools.

Development

Building
# Build all components
go build -o bin/mfc ./cmd/server
go build -o bin/specloader ./utils/cmd

# Run tests
go test ./...
Updating Specifications

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:

# View draft update information
cat data/SPEC_METADATA.json | jq '.specs.draft'

To update the draft specification:

./bin/specloader spec --version draft
./bin/specloader embed --version draft
./bin/specloader embed --version draft-fine

To add a new specification version:

./bin/specloader spec --version 2025-12-15
./bin/specloader embed --version 2025-12-15
./bin/specloader embed --version 2025-12-15-fine

All specification extraction dates and source commits are automatically tracked in data/SPEC_METADATA.json.

Testing Tools

Test the server using the included test client:

# Build test client
go build -o bin/factcheck-curl ./cmd/factcheck-curl

# Test tools
./bin/factcheck-curl --cmd ./bin/mfc --data-dir ./data/embeddings tools/list
./bin/factcheck-curl --cmd ./bin/mfc --data-dir ./data/embeddings tools/call validate_content '{"content":"MCP is a protocol"}'

# Test prompts
./bin/factcheck-curl --cmd ./bin/mfc --data-dir ./data/embeddings prompts/list

# Get migration prompt with minimal parameters
./bin/factcheck-curl --cmd ./bin/mfc --data-dir ./data/embeddings prompts/get migrate-mcp-content '{"current_version":"2024-11-05","target_version":"draft"}'

# Get migration prompt with all parameters
./bin/factcheck-curl --cmd ./bin/mfc --data-dir ./data/embeddings prompts/get migrate-mcp-content '{
  "current_version": "2024-11-05",
  "target_version": "2025-06-18",
  "update_scope": "critical_only"
}'

Architecture

See DESIGN.md for the complete architecture documentation.

Environment Variables

  • OPENAI_API_KEY - Required for embedding generation and content validation
  • GITHUB_TOKEN - Optional, for higher GitHub API rate limits when extracting specs

License

MIT License. See LICENSE for details.

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