
Mcp Factcheck
io.github.carlisiaPublished by GitHub account carlisiav1.0.0Updated Oct 24, 2026
An MCP server that validates content against MCP specification using semantic search and AI
Overview
A local MCP server that fact-checks content about the Model Context Protocol against official spec versions using semantic search and AI validation.
- What you can do
- Validate MCP-related claims and multi-claim content, returning verdicts, corrections and confidence scores with a step-by-step workflow and best-practice checks. Quick-check single statements or questions with a concise pass/fail verdict and explanation. Search MCP specification versions by semantic similarity and list available versions with dates and the current one. Guide migration of MCP content between specification versions with a configurable update scope.
- When to use it
- Useful when writing or reviewing documentation, tutorials or code about MCP and you want claims checked against the official specification, or when migrating content from an older spec version to a newer one.
- Requirements
- Runs as a local process (stdio) on the desktop; the manifest lists a container image. Requires an OpenAI API key in OPENAI_API_KEY for embedding generation and content validation, so network access to OpenAI is needed. An optional GITHUB_TOKEN raises GitHub API rate limits when extracting specs.
Installation
In SourceWeft
- Open Mcp Factcheck in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
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
-
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
-
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
-
search_spec- Searches MCP specifications using semantic similarity- Returns most relevant specification sections
- Supports all specification versions
-
list_spec_versions- Lists available MCP specification versions- Shows version dates and descriptions
- Indicates which version is current
MCP Prompts Available
-
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 becritical_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 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:
- Install and start Phoenix:
- Update the Host config to send traces to Phoenix:
- 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
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:
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.
Testing Tools
Test the server using the included test client:
Architecture
See DESIGN.md for the complete architecture documentation.
Environment Variables
OPENAI_API_KEY- Required for embedding generation and content validationGITHUB_TOKEN- Optional, for higher GitHub API rate limits when extracting specs
License
MIT License. See LICENSE for details.
Source: README.md at commit a1e6bfc
Tools
0Version history
1- v1.0.0LatestSep 16, 2026
Score
50% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
- Reached in the last 30 days25 pts
Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.
- Auth declared10 pts
Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.
- Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts